Rapid determination method for pit age of Luzhou-flavor liquor pit mud

Abstract

The invention discloses a method for rapidly determining the age of pit mud of Luzhou-flavor liquor, which comprises the following steps: taking pit mud of different age as standard samples, and carrying out headspace sampling to obtain volatile components of each standard sample; the method comprises the following steps: analyzing and collecting a two-dimensional volatile component top view of a standard sample and collected data of each volatile component through gas chromatography-ion migration chromatography, comparing the collected data with an NIST database and an IMS database by adopting VOCal data analysis software, and carrying out qualitative analysis on the volatile components to obtain a qualitative result; according to the qualitative result and the ion peak intensity of the corresponding volatile component, analyzing the volatile component by using a Galley Plot plug-in to obtain a fingerprint spectrum, and determining a high-content substance in the standard sample through spectrogram difference analysis and taking the high-content substance as a characteristic volatile component of the standard sample; a chemometrics method is adopted, a Dynamic plug-in is used for conducting PCA clustering analysis on the ion peak intensity of all volatile components of each standard sample, rapid classification of pit mud of different pit ages is achieved, the pit age attribution of the pit mud sample to be detected is determined, and rapid pit age determination is achieved.

Description

Technical Field

[0001] The invention belongs to the technical field of analysis and detection, and more specifically relates to a method for quickly determining the cellar mud and cellar age of Luzhou-flavor liquor. Background Art

[0002] Cellar mud is the basis for the production of Luzhou-flavor liquor, and its aging directly affects the quality of the liquor. Cellar mud is rich in brewing microbial flora, and high-quality cellar mud is the prerequisite for producing high-quality liquor. The cellar age of the cellar mud is positively correlated with the quality of the cellar mud to a certain extent, but the cellar age of the cellar mud has always been identified by manual sensory identification. The manual sensory identification method has a large error due to the subjectivity of the evaluation process. Simple and fast cellar mud age identification technology is an important demand for cellar mud quality identification.

[0003] In the field of cellar mud age identification technology research, there is currently no applicable national standard. The main identification technologies proposed by researchers include: A patent application document with announcement number CN102226754B discloses a method for determining the cellar mud age of Luzhou-flavor liquor, which combines diffuse reflectance near-infrared spectroscopy with principal component analysis to establish a feature projection map and build a database, and judge the cellar age of the cellar mud by comparing the spatial distribution. A patent application document with announcement number CN107513572B discloses a method for identifying the cellar mud age, which is based on the metabolic fingerprint cluster analysis of the dominant microbial community of the cellar mud, and is identified through an automated cellar mud age identification system, which can identify the quality and maturity of the cellar mud. A patent application document with publication number CN113689913A discloses a method for determining the cellar age of Luzhou-flavor liquor cellar mud. The method detects the bacterial microbial community of the cellar mud, collects cellar mud sample data, processes the collected sample data by amplicon data to obtain an OTU table, then screens modeling variables in the OTU table through random forest regression, establishes a measurement model based on the modeling variables, and determines the cellar age of the cellar mud through the measurement model.

[0004] The above methods provide different identification methods for the identification of cellar mud age, but all methods fail to clearly define the changes in volatile components of cellar mud of different cellar ages. At the same time, the determination and detection process of cellar mud microbial communities is cumbersome and inefficient, and cannot provide timely and accurate guidance for production.

[0005] So far, there is no relevant literature on the use of ion mobility spectrometry to analyze the volatile components of cellar mud of different cellar ages, nor is there any report on the use of ion mobility spectrometry combined with principal component analysis to determine the cellar age of Luzhou-flavor liquor cellar mud.

[0006] At present, in production practice, the age of cellar mud is mainly determined by professionally trained and experienced wine experts, but the manual determination method is inevitably affected by human factors. In order to achieve more accurate analysis, some physical and chemical index tests have been developed for cellar mud, such as moisture, pH and ammonium nitrogen, but the detection cycle is long, the operation is cumbersome, and the labor and consumables cost is high. At the same time, the cellar mud samples are easily dried and deteriorated after long-term exposure after sampling, which is not conducive to rapid and accurate analysis. Summary of the invention

[0007] The present invention aims to avoid the deficiencies of the above-mentioned prior art and to provide a method for quickly determining the cellar age of Luzhou-flavor liquor mud with a fast and sensitive detection process, thereby effectively utilizing the test results of the volatile components of the cellar mud and the cellar age to guide production in a timely and accurate manner.

[0008] The present invention adopts the following technical solutions to achieve the purpose of the invention:

[0009] The method for rapidly determining the cellar age of Luzhou-flavor liquor cellar mud of the present invention is characterized in that it comprises the following steps:

[0010] Step 1, selecting pit mud with pit ages of one year, two years, ten years and twenty years as standard samples M;

[0011] Step 2: using a head space sampling device to collect volatile components of each standard sample M by head space sampling to obtain the volatile components N of each standard sample;

[0012] Step 3: Performing gas chromatography-ion mobility chromatography analysis on the volatile components N of each standard sample obtained in step 2 by using gas phase ion mobility spectrometry, collecting a two-dimensional volatile component top view of each standard sample M and collected data of each volatile component, wherein the collected data includes the retention time T1, migration time T2, migration rate V and ion peak intensity Q of each volatile component;

[0013] Step 4: Using VOCal data analysis software, the collected data in step 3 are compared with the NIST database and IMS database built into the GC-IMS, and the volatile components in each standard sample M are qualitatively analyzed to obtain qualitative results;

[0014] Step 5: According to the qualitative results obtained in step 4 and the ion peak intensity Q of the corresponding volatile components, the Gallery Plot plug-in is used to analyze the volatile components to obtain the fingerprint spectrum P;

[0015] Step 6: For the fingerprint spectrum P of the standard sample obtained in step 5, a chemometric method is used to perform PCA cluster analysis on the ion peak intensity Q of all volatile components of each standard sample M using the Dynamic plug-in to achieve rapid classification of pit muds of different pit ages;

[0016] Step 7, process the cellar mud R to be tested according to steps 2 to 5 in claim 1 to obtain a fingerprint spectrum P of the cellar mud R to be tested, substitute the fingerprint spectrum P of the cellar mud R to be tested into the PCA cluster analysis result in step 6, and the cellar age whose two-dimensional principal component projection map of the cellar mud to be tested is closest to the two-dimensional principal component projection map of the PCA cluster analysis is the cellar age of the cellar mud to be tested, thereby realizing rapid determination of the cellar age.

[0017] The method for rapid determination of cellar age of Luzhou-flavor liquor pit mud of the present invention is also characterized in that: in step 2, the process conditions for headspace sampling are set as follows: 3.0 g of sample is weighed and placed in a 20 mL headspace bottle, the incubation temperature is set to 80° C., the incubation time is 15 min, the injection needle temperature is 85° C., and the incubation speed is 500 rpm.

[0018] The method for rapid determination of cellar age of Luzhou-flavor liquor of the present invention is also characterized in that: in step 3, the process conditions of gas chromatography analysis in the gas chromatography-ion mobility chromatography analysis are set as follows:

[0019] Set the analysis time to 40 minutes and the split mode to non-split;

[0020] The column type was: DB-WAX, 30 m, ID: 0.53 mm, film thickness 1.0 μm, column temperature 60 °C;

[0021] The carrier gas was nitrogen; it was maintained at 2 mL / min during 0-2 min; it was linearly increased to 10 mL / min during 2-10 min; it was linearly increased to 100 mL / min during 10-30 min; it was maintained at 100 mL / min during 30-40 min.

[0022] The method for rapid determination of the cellar age of Luzhou-flavor liquor of the present invention is also characterized in that: in the step 2, the process conditions of the ion mobility spectrometry analysis in the gas chromatography-ion mobility chromatography analysis are set as follows: the migration tube length is 98 mm; the voltage is 500 V / cm; the temperature is 45° C.; the drift gas is N 2 ; The drift gas flow rate is 75 mL / min.

[0023] The method for rapid determination of cellar mud age of Luzhou-flavor liquor of the present invention is also characterized in that: in step 5, the spectrum difference analysis is performed using a Reporter plug-in.

[0024] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0025] 1. The present invention uses pit mud of different pit ages as standard samples, and adopts gas phase ion mobility spectrometry (GC-IMS) technology to count and analyze its volatile components. The detection process is fast and sensitive. By analyzing the composition of volatile components of pit mud of different pit ages and determining the pit age, the research results can provide technical guidance for the volatile component analysis, pit age determination and maintenance of pit mud.

[0026] 2. The present invention can clarify the categories and differences of volatile components of pit muds of different pit ages by establishing GC-IMS characteristic spectra of pit muds of different pit ages.

[0027] 3. The method of the present invention is a combination of headspace-gas chromatography-ion mobility spectrometry technology to realize principal component analysis, which can realize rapid analysis of volatile components in pit mud of different pit ages and identification of pit ages, and has good application prospects in volatile component analysis and quality evaluation of pit mud. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a top view of the two-dimensional volatile components of standard samples of pit mud of different pit ages;

[0029] Figure 2 It is the fingerprint of standard samples of pit mud of different pit ages;

[0030] Figure 3 It is the two-dimensional principal component projection diagram of pit mud of different pit ages; DETAILED DESCRIPTION

[0031] The method for rapidly determining the cellar age of Luzhou-flavor liquor in the present embodiment comprises the following steps:

[0032] Step 1: Select pit mud with pit ages of one, two, ten and twenty years as standard samples M.

[0033] Step 2: Use a headspace sampling device to collect volatile components of each standard sample M by headspace sampling to obtain the volatile components N of each standard sample; set the process conditions of headspace sampling as follows: weigh 3.0 g of sample and place it in a 20 mL headspace bottle, set the incubation temperature to 80° C., the incubation time to 15 min, the injection needle temperature to 85° C., and the incubation speed to 500 rpm.

[0034] Step 3: Perform gas chromatography-ion mobility chromatography analysis on the volatile components N of each standard sample obtained in step 2 using gas phase ion mobility spectrometry, perform parallel measurements on each standard sample, collect a two-dimensional volatile component top view of each standard sample M and collected data of each volatile component, the collected data including the retention time T1, migration time T2, migration rate V and ion peak intensity Q of each volatile component.

[0035] In this embodiment, the process conditions of gas chromatography analysis in gas chromatography-ion mobility chromatography analysis are as follows: analysis time: 40 min; split mode is non-split; chromatographic column type: DB-WAX, 30 m, ID: 0.53 mm, film thickness 1.0 μm, column temperature 60 ° C; carrier gas is nitrogen; maintain 2 mL / min from 0 to 2 min; linearly increase to 10 mL / min from 2 to 10 min; linearly increase to 100 mL / min from 10 to 30 min; maintain at 100 mL / min from 30 to 40 min.

[0036] The process conditions for ion mobility spectrometry analysis in gas chromatography-ion mobility chromatography analysis in this embodiment are as follows: the migration tube length is 98 mm; the voltage is 500 V / cm; the temperature is 45° C.; the drift gas is N 2 ; The drift gas flow rate is 75 mL / min.

[0037] Step 4: Using VOCal data analysis software, compare the data collected in step 3 with the NIST database and IMS database built into the GC-IMS, and obtain qualitative results by qualitatively analyzing the volatile components in each standard sample M.

[0038] Step 5: According to the qualitative results obtained in step 4 and the ion peak intensity Q of the corresponding volatile components, the Gallery Plot plug-in is used to analyze the volatile components to obtain the fingerprint spectrum P.

[0039] Step 6. For the fingerprint spectra P of the standard samples M of different cellar ages obtained in step 5, the chemometric method is adopted, and the Dynamic plug-in is used to perform PCA cluster analysis and similarity analysis on the ion peak intensity Q of all volatile components of each standard sample M to determine the type of unknown components. The "nearest neighbor" fingerprint analysis is used to calculate the Euclidean distance matrix between samples, and the "nearest neighbor" is found by retrieving the minimum distance. The measurement results of relatively close groups are observed compared with more distant groups, so as to achieve rapid classification of cellar muds of different cellar ages.

[0040] Step 7, process the cellar mud R to be tested in the same way as steps 2 to 5 to obtain the fingerprint spectrum P of the cellar mud R to be tested, substitute the fingerprint spectrum P of the cellar mud R to be tested into the PCA cluster analysis result in step 6, and the cellar age whose two-dimensional principal component projection map of the cellar mud to be tested is closest to the two-dimensional principal component projection map of the PCA cluster analysis is the cellar age of the cellar mud to be tested, thereby realizing rapid determination of the cellar age.

[0041] The volatile components measured in this embodiment include: ethyl valerate, ethyl butyrate, ethyl acetate, ethyl heptanoate, ethyl hexanoate, ethyl propionate, 2-dimethyl isoborneol, butyric acid, propionic acid, methyl benzoate, acetic acid, ethyl nonanoate, 1-octanol, ethyl octanoate, butyl hexanoate, ethyl lactate, 2-heptanol, butyl valerate, α-terpineol, 2-hexenal, 2-heptanone, butyl isovalerate, n-octyl acetate, heptyl acetate, methyl benzoate, amyl acetate, isobutyl butyrate, propyl butyrate, butyl acetate, ethyl 2-methylbutyrate, isobutyl acetate, 2-hexanone, camphene, 2-pentanone, 2-butanone, acetone, ethyl isobutyrate, 4-methyl-2-pentanone, 3-octanone, diallyl sulfide, propionaldehyde, 4-hexen-3-one and ethyl isovalerate.

[0042] Actual test example:

[0043] Weigh 3 g of sample and place it in a 20 mL headspace bottle. Incubate at 80 °C for 15 min. The test was carried out with each sample measured three times in parallel.

[0044] DB-WAX chromatographic column (30m, 0.53mm). Carrier gas / drift gas: nitrogen. Carrier gas flow rate:

[0045] Maintain 2 mL / min from 0 to 2 minutes; increase linearly to 10 mL / min from 2 to 10 minutes;

[0046] It increased linearly to 100 mL / min from 10 to 30 minutes and remained at 100 mL / min from 30 to 40 minutes;

[0047] Drift gas flow rate: 75 mL / min; column temperature: 60°C; IMS temperature: 45°C; injection needle temperature: 85°C; injection volume: 500 μL.

[0048] The NIST database and IMS database built into the software are used to perform qualitative analysis on the substances.

[0049] The Gallery Plot plug-in of the Laboratory Analytical Viewer (LAV) software was used to draw the GC-IMS fingerprints of each pit mud and to intuitively and quantitatively compare the differences in volatile organic compounds between samples. Dynamic PCA (dynamic principal component analysis) software was used to perform cluster analysis and similarity analysis on the samples, as well as to determine the types of unknown components and pit age.

[0050] The top view of the two-dimensional volatile components of standard samples of pit mud of different pit ages is shown in Figure 1 , Figure 1Each point on both sides of the RIP (the red vertical line at 1.0 on the horizontal axis, with a drift time of about 7.97ms) represents a volatile organic compound. The color represents the concentration of the substance, white means a lower concentration, red means a higher concentration, and the darker the color, the higher the concentration.

[0051] The fingerprints of standard samples of pit mud of different pit ages are shown in Figure 2 ( Figure 2 The peak numbers in the figure are consistent with those in Table 1). Figure 2 Each row in the shown spectrum represents a sample. From top to bottom, No. 1 to 6 are 1-year-old pit mud, No. 7 to 12 are 2-year-old pit mud, No. 13 to 18 are 10-year-old pit mud, and No. 19 to 24 are 20-year-old pit mud. Each sample was measured in parallel three times; each column represents a signal peak. Figure 2 It contains all the signal peaks that can be detected under the detection conditions, and can intuitively show the composition and relative content of volatile substances in different samples. As can be seen from the figure, pit muds of different pit ages contain common volatile organic compounds with certain similarities. The substances shown in the yellow box are common and similar components in different samples. There are also certain differences in the position, quantity, intensity and time of ion peaks between pit muds of different pit ages. The substances shown in the red box in the figure are characteristic volatile components in each sample, and their relative content in each sample is significantly higher than that in other samples.

[0052] Figure 3 The two-dimensional principal component projection diagram of the pit mud. The horizontal axis is PCA1, that is, the projection score on principal component 1; the vertical axis is PCA2, that is, the projection score on principal component 2; A, B, C, and D represent the pit mud samples with a pit age of 1 year, 2 years, 10 years, and 20 years, respectively.

[0053] Table 1 Qualitative analysis of volatile compounds

[0054]

[0055]

[0056]

[0057] The qualitative analysis results of the volatile compounds in the samples are shown in Table 1. A total of 50 components were identified, including 24 esters, 8 ketones, 3 acids, 4 alcohols, 2 aldehydes, 1 terpene, and 1 ether. Due to the presence of monomers, dimers, and even polymers, several single compounds may produce multiple signals or spots, which are attributed to their different concentrations.

[0058] The invention realizes the rapid analysis of volatile components in pit mud of different pit ages and the identification of pit ages, and has good application prospects in the analysis of volatile components and the quality evaluation of pit mud.

Claims

1. A method for rapidly determining the cellar age of Luzhou-flavor liquor, characterized in that The steps include: Step 1, selecting pit mud with pit ages of one year, two years, ten years and twenty years as standard samples M; Step 2, using a head space sampling device to collect volatile components of each standard sample M by head space sampling to obtain the volatile components N of each standard sample; Step 3: Performing gas chromatography-ion mobility chromatography analysis on the volatile components N of each standard sample obtained in step 2 by using gas phase ion mobility spectrometry, collecting a two-dimensional volatile component top view of each standard sample M and collected data of each volatile component, wherein the collected data includes the retention time T1, migration time T2, migration rate V and ion peak intensity Q of each volatile component; Step 4: Using VOCal data analysis software, the collected data in step 3 are compared with the NIST database and IMS database built into the GC-IMS, and the volatile components in each standard sample M are qualitatively analyzed to obtain qualitative results; Step 5: According to the qualitative results obtained in step 4 and the ion peak intensity Q of the corresponding volatile components, the Gallery Plot plug-in is used to analyze the volatile components to obtain the fingerprint spectrum P; Step 6: For the fingerprint spectrum P of the standard sample obtained in step 5, a chemometric method is used to perform PCA cluster analysis on the ion peak intensity Q of all volatile components of each standard sample M using the Dynamic plug-in to achieve rapid classification of pit muds of different pit ages; Step 7, process the cellar mud R to be tested according to steps 2 to 5 in claim 1 to obtain a fingerprint spectrum P of the cellar mud R to be tested, substitute the fingerprint spectrum P of the cellar mud R to be tested into the PCA cluster analysis result in step 6, and the cellar age whose two-dimensional principal component projection map of the cellar mud to be tested is closest to the two-dimensional principal component projection map of the PCA cluster analysis is the cellar age of the cellar mud to be tested, thereby realizing rapid determination of the cellar age.

2. The method for rapidly determining the cellar age of Luzhou-flavor liquor according to claim 1, wherein: The process conditions for headspace injection in step 2 are as follows: weigh 3.0 g of sample and place it in a 20 mL headspace bottle, set the incubation temperature to 80° C., the incubation time to 15 min, the injection needle temperature to 85° C., and the incubation speed to 500 rpm.

3. The method for rapidly determining the cellar age of Luzhou-flavor liquor according to claim 1, wherein: In step 3, the process conditions of gas chromatography analysis in the gas chromatography-ion mobility chromatography analysis are set as follows: Set the analysis time to 40 minutes and the split mode to non-split; The column type was: DB-WAX, 30 m, ID: 0.53 mm, film thickness 1.0 μm, column temperature 60 °C; The carrier gas was nitrogen; it was maintained at 2 mL / min during 0-2 min; it was linearly increased to 10 mL / min during 2-10 min; it was linearly increased to 100 mL / min during 10-30 min; it was maintained at 100 mL / min during 30-40 min.

4. The method for rapidly determining the cellar age of Luzhou-flavor liquor according to claim 1, wherein: In the step 2, the process conditions of the ion mobility spectrometry analysis in the gas chromatography-ion mobility chromatography analysis are set as follows: The length of the migration tube is 98 mm; the voltage is 500 V / cm; the temperature is 45°C; the drift gas is N2; and the drift gas flow rate is 75 mL / min.

5. The method for rapidly determining the cellar age of Luzhou-flavor liquor according to claim 1, wherein: In step 5, the spectrum difference analysis is performed using a Reporter plug-in.

Images