62 results about "Liquor sample" patented technology

The invention discloses a white spirit flavor recognition method based on machine learning, and belongs to the technical field of food detection and artificial intelligence. Aiming at the problems of high subjectivity of manual evaluation, low efficiency of mass spectrometry, noise sensitivity of a machine learning model and the like in the prior art, the method provides a solution integrating solvent background deduction and feature weight screening. The method specifically comprises the following steps: diluting a white spirit sample with methanol according to a volume ratio of 1: 10, collecting mass spectrum data through GC-MS, and dynamically deducting a methanol background peak; a BP neural network (GABP) optimized by a genetic algorithm is utilized to automatically analyze a weight coefficient of each molecular peak to flavor classification, and key features are screened; a classification model is constructed based on XGBoost, and parameters are optimized through cross validation, so that automatic judgment of the flavor type, authenticity and quality of the white spirit is realized. According to the method, through data dimension reduction and model collaborative optimization, the overfitting problem caused by high noise and high redundancy of mass spectrum data is solved, the classification accuracy is remarkably improved, and the method can be extensively applied to white spirit brand identification, process optimization and market quality supervision.

The invention discloses a method for analyzing and detecting hydroxyl and amino substances in Baijiu and application, and relates to the technical field of Baijiu detection and analysis. The method comprises the following steps: carrying out derivatization reaction on bromine nicotinoyl chloride and hydroxyl and amino compounds in a white spirit sample to obtain a derivatized white spirit sample, carrying out data acquisition on the derivatized white spirit sample by utilizing a UPLC-HRMS platform, screening derivatized products by virtue of bromine isotope mass spectrum peaks, and determining the content of the bromine isotope mass spectrum peaks. And finally, performing high-coverage annotation on hydroxyl and amino compounds in the white spirit by combining multi-dimensional information including retention time, a primary mass spectrum and a secondary mass spectrum. The derivatization reaction does not need heating, the reaction time is short, a rapid and mild derivatization method is established, the loss of volatile compounds is avoided, and the analysis efficiency is improved; according to the invention, the natural isotope characteristics of bromine atoms are utilized to efficiently screen labeled compounds, and other heavy isotope labeling reagents are prevented from being additionally synthesized and used.

The invention discloses a Maotai-flavor liquor process category and authenticity identification model construction method, an identification method, an identification device and equipment. The method comprises the following steps: acquiring data of liquor samples; preprocessing the sample data to obtain preprocessed sample data; the preprocessed sample data are input into an initial identification model constructed based on a graph neural network or a partial least square discrimination method, the initial identification model is trained, target identification models are obtained, and the target identification models comprise a gas chromatography identification model, an ion chromatography identification model and / or a three-dimensional fluorescence spectrum identification model. According to the method, multiple analysis technologies such as GC, IC and EEM and a chemometrics modeling analysis module are adopted, analysis results of different technologies are mutually verified, a target identification model with high prediction precision is constructed, and accurate identification of the process category and authenticity of the Maotai-flavor liquor is realized.

The invention provides a Chinese liquor AI evaluation system and method based on multi-modal data fusion, and the system comprises a data collection module which is used for collecting multi-modal data of a liquor sample; the data preprocessing module is used for preprocessing the collected multi-modal data; the feature fusion module is used for fusing the multi-modal data and constructing feature vectors comprehensively reflecting the quality features of the white spirit; the evaluation model is used for learning a mapping relation between the multi-modal characteristics of the white spirit and the quality grade and evaluating the quality of the white spirit; and the output module is used for outputting the liquor quality identification result. Through multi-modal data fusion and a deep learning algorithm, the subjectivity of artificial evaluation is effectively reduced, the accuracy of an identification result is improved, automatic identification of the quality of the white spirit is realized, the identification efficiency is greatly improved, the identification cost is reduced, the quality of the white spirit can be comprehensively and systematically evaluated, and the method has an important application value.

The invention discloses a baijiu storage year prediction method, and relates to the technical field of baijiu year analysis, the method comprises the following steps: sample data acquisition and pretreatment: extracting flavor substance information in a baijiu sample through GC-O-MS and GC-FID technologies; key flavor substances are screened, AEDA and OAV are adopted for analysis, and flavor substances with significant differences in baijiu of different years are recognized and screened out; feature data extraction and optimization: key flavor substance features related to storage years are determined through K-MEANS clustering and OPLS-DA analysis; prediction model construction and training: based on the screened key flavor substance data, adopting a machine learning algorithm to establish and optimize a prediction model of the storage years of the Baijiu; and year prediction and output: inputting the flavor substance data of the white spirit sample to be predicted into the trained prediction model, and outputting and storing a year prediction value. Therefore, the problems that in the prior art, storage year labeling lacks objective basis, the prediction technology is limited greatly, and it is difficult to accurately predict the storage year of Baijiu are solved.

The invention discloses a molecular simulation and flavor perception-based beer umami peptide efficient identification method, and relates to the technical field of food flavor analysis and bioinformatics. The method comprises the following steps: performing liquid-liquid extraction and mass spectrum analysis on a beer sample to obtain a polypeptide sequence; screening the umami active peptide based on a UMPred FRL model; the method comprises the following steps: constructing a T1R1 / T1R3 receptor homologous model, and screening a peptide fragment of which the binding energy is lower than-25kcal / mol by adopting a CDOCKER semi-flexible docking mode; screening a stable peptide of which the delta Gbind is lower than-50kcal / mol through molecular dynamics simulation and MM / GBSA calculation; and finally, the umami characteristic is verified by combining an electronic tongue and a sensory test. The screened peptide fragment can be used for improving umami perception and taste balance of beer.

The invention discloses a method, equipment, medium and product for predicting the year of Maotai-flavor liquor, and relates to the technical field of chromatography and spectrum, chemometrics and artificial intelligence analys.The method comprises the steps that a chromatographic separation technology is utilized, chromatographic data and spectrum data of a Maotai-flavor liquor sample to be detected are collected, the chromatographic data are preprocessed, and the year of the Maotai-flavor liquor sample to be detected is obtained; determining the preprocessed data; decomposing and processing the three-dimensional fluorescence spectrum data based on a high-order cyclic factor algorithm, and determining a decomposition result; taking the processed data as four trained Bayesian network models, and outputting four year prediction results of the Maotai-flavor liquor; and taking the median of the four year prediction results of the Maotai-flavor liquor as the final year prediction result of the Maotai-flavor liquor sample to be detected. According to the method, the year prediction accuracy and prediction efficiency of the Maotai-flavor liquor can be improved.

The present application belongs to the technical field of food safety rapid detection, and discloses a liquor harmful substance synchronous identification method based on gas phase diffusion pretreatment. The present application utilizes the physical characteristics that the volatility of methanol and formaldehyde is significantly higher than that of ethanol and esters, carries out gas phase diffusion pretreatment under the condition that a closed container is at 40 DEG C to 60 DEG C, makes methanol and formaldehyde preferentially volatilize and be captured by two independent absorption chromogenic liquids respectively, makes ethanol and esters mainly remain in the liquor sample liquid, and the ethanol concentration in the absorption liquid is relatively reduced. Thus, the chromogenic reaction is carried out in the absorption liquid system in which the ethanol concentration is significantly reduced, and it is not necessary to dilute the liquor sample to low alcohol degree in a large amount, so that the technical problem that the traditional colorimetric method is seriously interfered by high alcohol degree ethanol and ester matrix is fundamentally solved.

The invention discloses a pyrazine-flavor-based multi-mode intelligent identification method for a Maotai-flavor liquor process. The method comprises the following steps: pretreatment: pretreating Maotai-flavor liquor samples of different brewing processes; collecting sensory data of electronic noses and electronic tongues of Maotai-flavor baijiu of different brewing processes; establishing a liquid phase detection method for the characteristic components of the alkylpyrazine in the Maotai-flavor liquor; verifying a component analysis method through precision, stability and repeatability experiments; component quantitative analysis based on liquid chromatography fluorescence detection; performing clustering and difference evaluation on Maotai-flavor liquor samples of different brewing processes by adopting multivariate statistical analysis; establishing a Maotai-flavor liquor process identification model: utilizing VIPgt in multivariate statistics; establishing different machine learning multi-classification models for different brewing processes of Maotai-flavor liquor according to the common characteristics of 1, and performing multi-model comparison; and based on the optimal performance classification model, establishing an SHAP model of the Maotai-flavor liquor brewing process identification model, and globally explaining the identification model by adopting an SHAP algorithm.

The invention belongs to the technical field of baijiu storage year prediction, and particularly relates to a baijiu storage year prediction method based on baijiu flavor substances. According to the baijiu storage year prediction method provided by the invention, the storage year of the baijiu sample to be detected is obtained by inputting the quantitative data of the key characteristic substances into the baijiu storage year prediction model. According to the method, the quantitative characteristics of the representative flavor substances in the Baijiu sample serve as input variables, the Baijiu storage year prediction model is established, the model has high generalization ability, in a test set, the model is simplified, high-precision prediction with the mean absolute error (MAE) being 0.58 and the determination coefficient (R2) being 0.98 is achieved, and the storage year of an unknown Baijiu sample can be accurately predicted.

The invention provides a method for rapidly analyzing the total ester content in raw liquor, and relates to the technical field of liquor detection. The method comprises the following steps: measuring the content of target esters in raw liquor; calculating the total ester content in the raw liquor according to a calculation formula of the total ester content; the calculation formula of the total ester content is shown in the specification; wherein X is the total ester content in the raw liquor, and the unit is g / L; ci is the content of target esters in the raw white spirit, and the unit is g / L; mi is the molar mass of the target ester in the raw white spirit, and the unit is g / mol; m ethyl acetate is the molar mass of ethyl acetate, and the unit is g / mol. According to the technical scheme provided by the invention, the content of the main esters can be directly detected only by taking the white spirit raw wine sample, the whole process takes about 30 minutes, and the detection can be successful once, fast and accurate.

The invention relates to the technical field, discloses a method for simultaneously determining 13 terpene compounds in Maotai-flavor baijiu, aims at exploration and optimization of pretreatment steps and chromatographic conditions, and aims to establish a stable and reliable detection method for the terpene compounds in the baijiu. And collection of terpene compound content data is carried out for representative Maotai-flavor white spirit samples, so that some technical support and data reference can be provided for research on white spirit quality improvement.

The invention relates to the technical field of food detection, and particularly discloses a method for identifying Luzhou-flavor liquor, which comprises the following steps: acquiring a plurality of different types of Luzhou-flavor liquor samples as a training set; carrying out non-targeted metabonomics analysis on the training set samples by adopting ultra-high performance liquid chromatography-tandem mass spectrometry, detecting non-volatile compounds in the training set samples, and obtaining composition and relative content data of the training set samples; based on the training set sample information and the non-volatile compound detection result, establishing a qualitative identification model of the Luzhou-flavor liquor by using an orthogonal partial least square discriminant analysis method; and performing non-targeted metabonomics analysis on a to-be-detected Luzhou-flavor liquor sample, and inputting obtained data into the qualitative identification model of the Luzhou-flavor liquor to obtain category information of the Luzhou-flavor liquor. According to the method provided by the invention, the established qualitative identification model of the Luzhou-flavor liquor based on different alcoholic strengths, producing areas and brands is reliable and good in predictability, and a new method can be provided for the qualitative identification of the Luzhou-flavor liquor.

The invention provides a volatile matter detection method for different rounds of baijiu base liquor and a flavor difference analysis method for baijiu. The volatile matter detection method for different rounds of baijiu base liquor comprises the following steps: S01, taking different rounds of baijiu base liquor, and correspondingly preparing a plurality of different rounds of baijiu samples by adopting a closed volatilization balance mode; s02, respectively detecting volatile matters in the plurality of different rounds of white spirit samples by adopting a gas chromatograph-ion mobility spectrometry combined instrument to obtain detection data, and S03, carrying out data processing and qualitative analysis on the detection data corresponding to the different rounds of white spirit samples in S20 by adopting VOCal software to obtain the volatile matters in the plurality of different rounds of white spirit samples. Two-dimensional spectrograms of the volatile matters in the white spirit samples in different rounds, difference spectrograms of the volatile matters in the white spirit samples in different rounds and fingerprint spectrums of the volatile matters in the white spirit samples in different rounds are obtained. Complex volatile component information is presented in the form of visual images and data, the visualization degree is high, identification of different rounds of base liquor of Baijiu is facilitated, and rapid detection of flavor quality of different rounds of base liquor is realized.

The invention relates to the technical field of wine making, and discloses a volatile sulfide-based white wine fermentation workshop process evaluation method and system, and aims to solve the problems of low efficiency and accuracy of the existing method, and the scheme mainly comprises the following steps: obtaining fermented grain samples from fermentation cellars of at least two workshops, and distilling to obtain raw wine samples; detecting the content of various target volatile sulfides, and constructing a feature vector; training a workshop identification model by using the historical sample with the workshop identifier; statistical analysis is carried out on historical feature vectors according to the workshops, and a volatile sulfide fingerprint template library of each workshop is established; sampling and detecting a batch to be evaluated by adopting the same simplification mode, constructing a feature vector, identifying a workshop to which the batch belongs through a model, comparing the feature vector with a fingerprint template of the workshop, and calculating a deviation index; and judging whether the process state is normal or abnormal according to whether the deviation exceeds a threshold. According to the method, the efficiency and accuracy of white spirit fermentation workshop process evaluation are improved.

The invention relates to a method for quantifying ultra-trace bisphenol compounds in wine, which comprises the following steps: 1, sample pretreatment: concentrating a to-be-detected wine sample to obtain a concentrated solution, carrying out constant volume treatment on the concentrated solution, carrying out refrigerated centrifugation treatment on the concentrated solution subjected to the constant volume treatment, and taking supernate obtained after the centrifugation treatment as a to-be-analyzed solution; wherein a constant volume solvent adopted in the constant volume treatment is methanol; and quantifying the sample: carrying out quantitative analysis on the to-be-analyzed solution by adopting a chromatography-mass spectrometry method. According to the research, a sample is pretreated by concentration; according to the method, the specific variety of bisphenol compounds are rapidly screened through chromatography-mass spectrometry, the method which is wide in variety coverage range, rapid, accurate and capable of quantifying the bisphenol compounds is established, and the method can be used for risk screening of ultra-trace bisphenol and derivatives thereof in Baijiu.

The present invention belongs to the field of detection technology, and particularly relates to a detection method for the content of bioactive peptides in wine. Aiming at the technical problems that there are few reports on the detection method for the content of bioactive peptides in wine and the detection sensitivity is low, the present invention provides a detection method for the content of bioactive peptides in wine, which is to purify and enrich the bioactive peptides in wine through an SPE column, and then perform qualitative and quantitative determination by using an ultra-high performance liquid chromatography tandem mass spectrometer. The method of the present invention can accurately determine the content of bioactive peptides in wine samples, provide reliable technical support for the analysis and research of bioactive substances in wine, and has important significance for studying the health promotion effect of wine.

The utility model provides a grape wine sample processing device, which belongs to the field of grape wine and comprises a shell and a support plate, the support plate is fixedly connected to the top of the shell, a processing component is arranged on the outer wall of the support plate, and the processing component consists of a reciprocating unit and a rotating unit. According to the wine sample filtering device disclosed by the utility model, the containing bin is arranged, and the containing bin is connected with the shell in a clamping manner, so that after a wine sample is filtered, the downward pressing piece is separated from the containing bin, and the containing bin can be taken out from the interior of the shell in a sliding manner and replaced; the bottom bin is arranged, the bottom bin is connected with the shell through bolts, after the wine samples are filtered, the bottom bin can be taken out by taking down the bolts, an operator can conveniently clean the interior of the shell, and the situation that the wine samples are mixed up is avoided.

The invention relates to the field of liquor identification methods, in particular to a method for constructing a model for identifying authenticity of Maotai-flavor liquor, which is characterized by comprising the following steps of: 1, collecting carbon isotope data of a sample: measuring delta 13C values of ethanol and flavor skeleton components in the liquor sample, and generating a stable carbon isotope data set of the Maotai-flavor liquor; 2, analyzing and screening characteristic variables based on a partial least square method; 3, constructing a machine learning model: importing the screened feature variables into the machine learning model, and training the feature variables through the machine learning model; and 4, model application: based on the trained machine learning model, importing the characteristic variables of the to-be-detected wine sample into the model for identification, and obtaining an identification result of the to-be-detected wine sample. According to the method, the delta 13C values of the ethanol and the flavor skeleton components of the ethanol in the Maotai wine are measured based on the stable isotope mass spectrometry technology, the model is constructed, irrelevant noise is eliminated in combination with PLS-DA analysis, and the robustness, stability and accuracy of the whole model are improved.

The invention belongs to the technical field of liquor analysis, and discloses a method for detecting liquor by adopting a liquor gas chromatographic analysis system. The method comprises the following steps: S1, collecting a white spirit sample, and carrying out dynamic adsorption and thermal desorption coupling treatment to obtain a target sulfide component which can be introduced into a chromatographic system; s2, establishing a gas chromatography and thermal desorption combined system, completing debugging, and establishing a quantitative reference basis for sulfide detection; s3, the pretreated target component is introduced into a chromatographic system, and signal acquisition is completed through double-column series separation; s4, preprocessing the collected detection signal, identifying a target sulfide characteristic peak and storing the target sulfide characteristic peak; s5, on the basis of the detection signal parameters and the calibration data, the actual concentration of the sulfide in the sample is obtained through a correction calculation formula; s6, summarizing detection data and comparing the detection data with the standard to complete sulfide standard exceeding judgment; and S7, verifying and confirming the effectiveness of the method through multi-dimensional verification, and inserting a quality control sample to monitor the stability of the detection process.

The invention discloses a white spirit flavor identification method based on dynamic contact angle characteristics, which comprises the following steps: dropwise adding a white spirit sample on the surface of a pretreated polymer substrate, recording dynamic change data of the droplet form and the contact angle under the conditions of constant temperature and constant humidity, and drawing a dynamic curve of the contact angle changing along with time; extracting an initial contact angle, a descending stage turning point time and a descending rate from the dynamic curve; and comparing the descending rate with a pre-established aroma type wetting dynamic relation model, and outputting an aroma type judgment result of the white spirit according to a judgment criterion. According to the method, the dynamic wetting behavior of the liquor droplets on the specific hydrophobic surface is analyzed, the characteristic parameters obviously related to the flavor type are extracted, and the objective discrimination model is established, so that rapid and lossless identification of the flavor type of the liquor is realized.

The invention relates to an evaluation and selection device for wine sample evaluation, which comprises a wine table and a heat preservation cover arranged on the wine table, and further comprises an olfaction identification mechanism arranged on the wine table, the smell identification mechanism comprises a clamping assembly arranged on the wine table and used for fixing the multiple wine storage devices, a fragrance smelling assembly arranged at ports of the wine storage devices, a lighting assembly arranged on one side of the clamping assembly, a volatilization assembly arranged on the fragrance smelling assembly and located in the wine storage devices, and a wall moistening assembly arranged in the volatilization assembly; the extraction assembly is arranged on the fragrance smelling assembly and located at the bottle neck position of the wine storage device; the wine rubbing assembly is arranged on the fragrance smelling assembly; the smell identification mechanism is arranged to be matched with the taste identification mechanism, so that the functions of reducing random diffusion of wine aroma in air and unifying the selection time of players are achieved, and the technical problems that the time interval before and after wine pouring is long, time is unfair, the wine flavor and the foreign flavor in an examination room are heavy, and the quality judgment of wine samples is affected are solved.

The invention discloses an automatic detection method and system for measuring the fatty acid value of rice, and the method comprises the steps: determining to-be-measured rice, and obtaining a to-be-measured rice leach liquor sample; a standardized optical environment is constructed, the illumination intensity is kept stable, and a stable vortex flow field is generated; determining identification information of a to-be-detected rice extract liquid sample and associating the identification information with the basic information; pulse type dropwise adding and reaction solution image acquisition are synchronously executed when dropwise adding is started; performing edge detection and liquid level identification on the acquired image to extract a liquid area image; liquid area image pixel data is converted to a Lab or HSV color space, and a background reference data set is established; calculating a color difference value in real time, establishing a color difference value trend curve, determining a color difference value change rate peak value, judging a titration end point in combination with an adaptive threshold value, and determining a titration amount; and according to the determined titer and the associated basic information of the rice leach liquor sample, inversely calculating the fatty acid value. According to the invention, the anti-interference capability and precision of rice fatty acid value determination are improved.

A method for identifying the age of white spirit comprises the following steps: S1, detecting Maotai-flavor white spirit standard samples of different ages by using a gas chromatography-mass spectrometry technology to obtain original detection data of flavor substances; s2, based on variable importance analysis of a random forest model, screening out key characteristic substances from the flavor substances, and carrying out normalization and centralization processing on the content of the screened characteristic substances; s3, constructing a random forest classification model by using an R language random Forest package, taking the content of the key characteristic substance as an input variable and taking the real age of the white spirit as an output variable; and S4, detecting the content of key characteristic substances in a white spirit sample to be detected, processing the key characteristic substances, inputting the processed characteristic data into the random forest classification model, and outputting a predicted spirit age. Compared with the prior art, the method has the advantages that the detection variable is reduced by 98.6%, the out-of-bag error (OOB) of the model is reduced from 55.56% to 11.11%, and the recognition accuracy of the test set is improved to 89%.

The invention discloses a method for rapidly detecting and analyzing quality indexes of Luzhou-flavor raw wine, relating to the technical field of wine detection and comprising the following steps: acquiring a transmission and reflection spectrogram of a Luzhou-flavor raw wine sample; obtaining the measured value of the content of the volatile component in the sample; processing the acquired transmission and reflection spectrogram; performing dimension reduction processing on the processed transmission and reflection spectrogram by means of an improved kernel partial least squares algorithm in combination with a competitive adaptive reweighted sampling method, and extracting a characteristic wavelength; establishing a quantitative detection model for different volatile components based on the extracted characteristic wavelength and the measured value of the volatile component content obtained in the step 2; and verifying and comparing the accuracy of the established different quantitative detection models, and selecting an optimal model for actual detection of the quality index of the strong-flavor raw wine. The method has the advantages of being rapid, accurate, low in cost and environmentally friendly, and can meet the requirement for rapid detection of quality indexes in the production process of the strong-flavor raw wine.

The invention provides a method for predicting relative complexity index of white spirit flavor, which comprises the following steps of: obtaining flavor substances and corresponding contents of a plurality of white spirit samples with the same flavor type through quantitative analysis, screening out the flavor substances representing the flavor type, normalizing the contents of the flavor substances representing the flavor type in all the white spirit samples, and calculating the relative complexity index of the white spirit flavor. The content of each flavor substance after normalization is obtained, the content of each flavor substance after normalization of the same white spirit sample is summed, the flavor relative complexity index of each white spirit sample is obtained, and on the basis, the flavor substance and the corresponding content of the white spirit sample are constructed as input, the flavor relative complexity index is used as an output flavor relative complexity index prediction model, and the flavor relative complexity index of the white spirit sample to be detected is predicted by the flavor relative complexity index prediction model, so that the problem that the flavor complexity of the white spirit cannot be accurately reflected in the prior art is solved; the method is suitable for predicting the relative complexity index of the white spirit flavor.

The invention discloses a method for improving flavor of rice-flavor liquor. The method comprises the following steps: S1, soaking rice, S2, steaming the rice, S3, spreading and airing, S4, stirring yeast, S5, saccharifying in a water bath, S6, filtering, S7, adding maltose, S8, sterilizing, S9, inoculating, S10, fermenting and S11, distilling, namely distilling fermentation liquor after fermentation to obtain a rice-flavor liquor finished product. Through a low-cost means of regulating and controlling the concentration of maltose, on the premise that exogenous bacteria are not introduced, yeast metabolism is regulated, synthesis of ester flavor substances is remarkably improved, generation of higher alcohols is reduced, the problems that traditional rice-flavor Baijiu is single in flavor, insufficient in esters and prone to drunkenness after being drunk are effectively solved, the technical path is simple, the cost is controllable, and the method is suitable for industrial production. Key indexes such as glycerol content, yeast activity and alcohol generation rate are remarkably improved, and the obtained wine sample is excellent in aroma, taste, style, aftertaste and the like and has good market competitiveness.

The invention discloses a wine sample quality evaluation method based on a slow-drunkenness and quick-waking mechanism, and belongs to the field of pharmacological research of wines. The method comprises the following steps: preparing various wine samples with uniform alcoholic strength; setting a plurality of dose gradients for the wine sample, and carrying out gavage treatment on the mouse; observing whether the mice are drunk after gavage, and calculating the drunkenness ratio of each group of mice, namely the drunkenness causing rate of the group; calculating a fitting equation according to the number and the drunkenness rate of the drunkenness mice of each dose of wine sample, and determining half of the drunkenness amount of each wine sample; according to the half drunkenness amount of each wine sample, estimating the minimum dose of each wine sample for enabling all mice to enter a drunkenness state; after the multiple groups of mice are subjected to intragastric administration according to the minimum dosage of each wine sample, the intragastric administration starting time point, the time point when the gait is unstable or the falling-down somnolence occurs and the waking time point of each mouse are recorded, and the drunkenness time and the sobering time of each wine sample are calculated; and evaluating the quality of various wine samples according to the drunkenness time and the sobering time.

The invention relates to a base wine grade discrimination model construction method, a base wine grade discrimination method, a base wine grade discrimination device, equipment and a storage medium. The method comprises the following steps: carrying out difference analysis on flavor component information of different grades of base liquor samples to obtain a plurality of first characteristics meeting a preset difference condition; analyzing correlation among the plurality of first features, and screening out a second feature from the plurality of first features according to a correlation analysis result; according to the influence of the number of the second features on the precision of the base wine grade discrimination model, screening a target number of third features from the plurality of second features; and according to the target number of third features, constructing a base liquor grade discrimination model for discriminating the grade of the base liquor. By adopting the method, the accuracy of the base wine grade discrimination model for discriminating the base wine grade can be improved.

The invention discloses a method for simultaneously detecting phenolic compounds and alcohol compounds in white spirit based on UPLC-QQQ-MS / MS, and belongs to the technical field of wine detection. The detection method comprises the following steps: taking a Baijiu sample, adding an isotope internal standard phenol-d6 solution and a 2-propanol-d8 solution, then adding a derivatization reagent and a sodium carbonate solution to adjust the pH value to be alkaline, carrying out a derivatization reaction, after the reaction is finished, adding a formic acid solution to terminate the reaction, and filtering through a membrane to obtain a to-be-detected solution; detecting the to-be-detected liquid by adopting UPLC-QQQ-MS / MS, and calculating the contents of the phenolic compounds and the alcohol compounds in the white spirit according to the peak area ratio of each compound in the detected to-be-detected liquid to the corresponding isotope internal standard substance and the standard curve model, the detection method can be used for simultaneously detecting 6 alcohol compounds and 10 phenolic compounds, and is high in accuracy, high in sensitivity, simple, convenient and easy to operate.