CN114414686B - Method for monitoring microbial growth metabolism in aroma type Daqu starter propagation process - Google Patents
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Abstract
The invention belongs to the technical field of biology, and particularly relates to a method for monitoring microbial growth metabolism in a yeast making process of strong-flavor Daqu. The method comprises the following steps: samples were collected and the underlying data was tested: step two: microorganism diversity PCoA principal coordinate analysis based on 16S and ITS amplicons; step three: microbial differential analysis based on LEfSe; step four: clustering characteristic flavor substances at each stage of front slow, middle stile and rear slow falling; step five: and carrying out correlation analysis on the characteristic microorganisms and the characteristic flavor substances. In actual production, the change condition of characteristic flavor substances in each fermentation stage can be detected to reflect the actual growth condition of characteristic microorganisms in each stage of the strong-flavor Daqu fermentation, so that a basis is provided for timely making process adjustment.
Description
Technical Field
The invention belongs to the technical field of biology, and particularly relates to a method for monitoring microbial growth metabolism in a yeast making process of strong-flavor Daqu.
Background
Daqu is used as a special saccharification starter for Chinese strong aromatic Chinese spirits, and provides rich bacterial systems and enzyme systems for the fermentation of the strong aromatic Chinese spirits. The 'qu fixed-fragrance type' proves the influence of Daqu on the style characteristics of white wine. The structure difference and succession rule difference of the Daqu microorganism flora endow the strong aromatic white spirit with various styles. The production of the strong-flavor Daqu is a typical open multi-strain solid state fermentation system, the fermentation mechanism is complex, and the process control is carried out by uncovering a grass curtain and opening and closing doors and windows in the process of preparing the Daqu so as to regulate the growth metabolism of the microorganism flora of the Daqu. At present, the monitoring of microorganisms and fermentation states in the whole industry is mainly based on sensory indexes, namely, fermentation conditions are judged by visually observing the distribution of hyphae in Daqu and combining sniffing Qu Xiang, so that process operation is regulated.
Although the sensory evaluation method relying on experience in the current industry has the advantage of rapidness, overcomes the defects of long time consumption, complicated operation, difficult timely guidance of production process operation and the like of detecting Daqu microorganisms by using a culturable method and DNA sequence analysis, has the limitations of poor reliability, low reproducibility and the like in judging by human sense because the relevance between flavor substance synthesis and growth and reproduction of Daqu microorganisms in the Daqu production process is not known deeply. The invention aims to judge the growth and metabolism conditions of characteristic microorganisms at each stage in the fermentation process of the Daqu by detecting the volatile substances of the Daqu at each stage of front buffer, middle support and rear buffer.
Disclosure of Invention
The present invention is based on the problems of the prior art and provides a method for monitoring microbial growth and metabolism during the process of making yeast with aroma type Daqu as defined in claim 1. The method can realize the timely monitoring and rapid evaluation of the fermentation state of microorganism growth and metabolism in the starter propagation process of the white wine industry, so as to make process adjustment in time and optimize the fermentation process.
In order to achieve the above object, the present invention has the following specific technical scheme:
a method for monitoring microbial growth metabolism in a process of preparing yeast by using aroma-type Daqu, which comprises the following steps:
step one: samples were collected and the underlying data was tested: and collecting Daqu samples in different time in the fermentation process of Daqu at different positions of a fermentation starter room, and respectively measuring flavor substance components (organic acid, amino acid and volatile flavor substances) and bacteria structure data of the collected samples to obtain a dynamic change result.
Step two: microbial diversity PCoA principal coordinate analysis based on 16S and ITS amplicons: clustering samples in different fermentation periods of front slow, middle stile and rear slow by using R language, so as to determine the composition characteristics of bacteria and fungi in each stage;
step three: microbial differential analysis based on LEfSe: firstly, verifying species with obvious abundance differences in Daqu at different stages by using a nonparametric Kruskal-Wallis rank sum test, then, using Wilcoxon to test the difference consistency of different species at different stages in the last step, and finally, estimating the influence of the abundance of each species on the difference effect by adopting linear regression analysis. Thus finding out characteristic species with significant differences in abundance at each stage of Daqu fermentation, namely, a boom;
step four: clustering characteristic flavor substances at each stage of front slow, middle stile and rear slow falling: using simca software, based on the detected flavor components, performing supervised orthorhombic least squares discriminant analysis on the flavor to obtain characteristic flavor components of each fermentation stage;
step five: performing correlation analysis on characteristic microorganisms and characteristic flavor substances: the spss software is used for carrying out correlation analysis based on the Spilman coefficient on characteristic microorganisms and characteristic flavor substances in each stage of front buffer, middle stile and rear buffer drop, and carrying out double-tail inspection; drawing a correlation cluster heat map by using R language, and further displaying the correlation between the R language and the R language in the process of fermenting the strong aromatic Daqu; screening characteristic microorganisms and characteristic flavor substances with extremely obvious correlation, and drawing a correlation network diagram by using Gephi software; and (3) finding out flavor substances which are extremely obviously related to characteristic microorganisms in each stage of pre-tempering, middle tempering and post tempering by combining network analysis results, and determining the content of the characteristic microorganisms which are extremely obviously related to the characteristic flavor substances by detecting the content of the characteristic flavor substances in actual production, so as to establish a judging method of the growth and metabolism of the characteristic microorganisms in the stage of the aroma type Daqu starter making process.
In the first step, sampling time points are set to be 0d, 6d, 16d and 29d according to the process characteristics of starter propagation (front buffer, middle stile and rear buffer), and four groups of parallel samples are made at each time point; sampling positions are four vertexes of the yeast room, and the yeast samples are taken from top to bottom from the center position, fully crushed and uniformly mixed, and the total of 16 yeast samples are obtained.
As a preferred embodiment of the present application, the flavoring agent described in step one comprises an organic acid and a volatile flavoring agent;
the detection method comprises the steps of respectively measuring dynamic changes of organic acid in the fermentation process of Daqu by using a high performance liquid chromatography technology, and quantifying by using a peak area external standard method; and (3) analyzing the change of volatile flavor substances of the Daqu samples in different fermentation periods by using a headspace solid-phase microextraction-gas mass spectrometry combined technology, comparing the obtained volatile components with a NIST library for analysis, determining the types of the volatile components with the matching degree of >80, and quantifying the types by an internal standard method.
As a preferred embodiment of the present application, the bacterial genus structure data in step one refers to the extraction of total DNA from samples using a modified CTAB extraction method, and the high throughput sequencing using an Illumina Miseq platform to obtain the diversity index of each microorganism.
As a better implementation mode in the application, the specific steps of the second step are that R language and Galaxy are used for respectively carrying out cluster analysis and linear discriminant analysis on microorganisms in the process of fermenting the aroma-type Daqu, so that the cluster analysis is carried out on the microorganisms in each fermentation stage, the place with obvious difference in the compositions of the microorganisms in different fermentation stages is found from the result, and further, characteristic microorganisms in each fermentation stage of the Daqu can be found through the linear discriminant analysis, wherein the earlier slow stage is rhizopus, streptomyces, aspergillus, saccharopolyspora, candida and candida, the new candida, the middle-stage is thermoascus, thermoactinomyces, aeromonas, flavobacterium and crohn Peng Site, and the later slow stage is bacillus, thermophilic fungi, acinetobacter and sub-sepium.
As a better implementation mode in the application, the specific steps of the step four are that R and SPSS software are used for carrying out correlation analysis on 15 characteristic microorganisms and characteristic flavor substances, rho is 0.6, and a correlation heat map is drawn;
there are 8 bacteria with significant correlation to characteristic flavors, p <0.005:
the abundance of streptomycete has very obvious positive correlation with acetaldehyde, octane ethyl ester, (E, e) -2, 4-hexadienoic acid, ethyl enoate, ethanol, phenethyl alcohol and phenethyl alcohol; the abundance of bacillus is only positively correlated with 2, 3-butanediol; the abundance of acinetobacter is significantly inversely related to ethanol, ethyl oleate, aminoalcohol, ethyl palmitate and linoleic acid; the saccharopolyspora, the crohn Peng Site genus and the thermoactinomycetes have extremely obvious positive correlation with ethyl octanate, phenethyl alcohol and phenylazetidine simultaneously; the abundance of aeromonas and flavobacterium is positively correlated with the content of ethanol and ethyl oleate.
There are 7 fungi that are significantly associated with characteristic flavors:
rhizopus is obviously positively correlated with 12 characteristic flavor substances in total, namely isoamyl alcohol, amyl acetate, phenylacetaldehyde, nonolactone propyl, 2-n-pentylurea, benzaldehyde, isovaleraldehyde, phenethyl alcohol, 2, 3-butanediol, trans-2, 4-decadienal, 2-methylnaphthalene and ethyl palmitate; aspergillus has a significant positive correlation with ethyl linoleate; the abundance of the thermoascus is obviously positively correlated with the content of ethanol, ethyl oleate and ethyl valerate; the abundance of thermophilic fungi is obviously positively correlated with the content of ethanol, ethyl oleate, ethyl octanoate and N-amidoalcohol; the abundance of candida is extremely obviously and inversely correlated with the content of 2-n-pentylurea, benzaldehyde, isovaleraldehyde, phenethyl alcohol, 2-phenylcrotonaldehyde and benzyl alcohol; the abundance of the new candida species is simultaneously and remarkably and negatively correlated with the content of isoamyl acetate, 3-hydroxy-2 butanone, isoamyl alcohol, amyl acetate, phenylacetaldehyde, acrylyl phosphite, 2-N-starch furan, benzaldehyde and isoamyl alcohol; the abundance of the genus Celastrus is also extremely significantly inversely correlated with the amount of 2-N-starch furan, benzaldehyde, isoamyl alcohol, phenethyl alcohol, benzyl alcohol, 2,3 butanediol, acetic acid, ethyl acetate, ethyl palmitate.
As a preferred embodiment of the present application, the specific steps of the fifth step are: and (3) carrying out correlation network analysis on the characteristic microorganisms with extremely obvious correlation and the characteristic flavor substances in the step four, and explaining the characteristic bacteria, fungi and dynamic changes of the characteristic flavor substances in each fermentation stage, so as to establish a novel distinguishing method of the strong aroma type Daqu stage characteristic microorganisms based on the microorganisms and the flavor substances.
As a preferred embodiment in the present application, it is that: the change condition of characteristic flavor substances in each fermentation stage is detected to reflect the actual growth condition of characteristic microorganisms in each stage of the strong-flavor Daqu fermentation so as to make process adjustment in time, and the product quality is ensured by stage controllable fermentation.
Compared with the prior art, the invention has the following positive effects:
compared with the traditional solid state fermentation process monitoring relying on sensory evaluation, the method provided by the invention is used for carrying out corresponding difference analysis on the whole fermentation process based on microorganisms and flavor substances, and the staged differences are quite obvious, and the results are relatively similar, so that the three stages of slow front, medium and slow rear of the strong-flavor Daqu fermentation process have obvious differences.
And (II) searching characteristic flavor substances and characteristic microorganisms in each fermentation stage through an orthogonal partial least squares model and LEfSe (linear discriminant analysis) based on the front, middle stile and rear slow landing stages.
And thirdly, finding out characteristic flavor substances with extremely obvious correlation between each fermentation stage and characteristic microorganisms through correlation analysis, and describing the correlation between characteristic species and characteristic flavor synthesis based on metabolome theory.
And fourthly, in actual production, the change condition of the characteristic flavor substances of each fermentation stage can be detected to reflect the actual growth condition of characteristic microorganisms of each stage of the strong-flavor Daqu fermentation so as to make process adjustment in time.
Description of the drawings:
FIG. 1 is a schematic flow chart of a method for monitoring microbial growth metabolism during the process of preparing yeast from strong aromatic Daqu.
FIG. 2 is a flow chart for analyzing and evaluating the variability of the process of making the aroma type Daqu
FIG. 3 is a graph showing the temperature change during the starter propagation
FIG. 4 is a graph showing the results of PCoA analysis of bacteria and fungi
FIG. 5 is a graph showing the LDA score of LEfSe (Linear discriminant analysis) for microorganisms
FIG. 6 is a graph of flavor-based clustering and OPLS-DA model
FIG. 7 is a correlation cluster heat map of the Szelman coefficients for all characteristic microorganisms and characteristic flavors
FIG. 8 is a network graph of the correlation of characteristic microorganisms with characteristic flavors having very significant correlation
Detailed Description
In order that the invention may be more readily understood, a further description of the invention will be provided below in connection with the detailed description. It should not be construed that the scope of the above subject matter of the present invention is limited to the following examples.
The percentages expressed in the present invention are weight percentages unless otherwise indicated.
Example 1 Heat season fermentation Daqu in Sichuan certain winery
Step one: and (3) collecting a strong-flavor Daqu sample, wherein the sample is collected from a starter making workshop of a certain well-known winery in Sichuan, taking out Daqu samples from four vertexes and the center position of a starter room from top to bottom, fully crushing and uniformly mixing, setting sampling time points to be 0d, 6d, 16d and 29d according to the process characteristics of starter making (front slow, middle straight and rear slow falling), and making four groups of parallel samples at each time point, wherein the temperature parameter change in the starter making process is shown in figure 2.
Step two: detecting the flavor substances, respectively measuring the dynamic change of the organic acid in the fermentation process of the Daqu by using a high performance liquid chromatography technology, and quantifying by using a peak area external standard method. And (3) analyzing the change of volatile flavor substances of the Daqu samples in different fermentation periods by using a headspace solid-phase microextraction-gas mass spectrometry (GC-MS), comparing the obtained volatile components with a NIST library for analysis, determining the types of the volatile components with the matching degree of >80, and quantifying by an internal standard method. The changes in the types and contents of the flavoring substances are shown in Table 1, and the types and contents of the organic acids are shown in Table 2.
Step three: the total DNA of the sample is extracted by adopting a modified CTAB extraction method, and the high-throughput sequencing is carried out by using an Illumina Miseq platform. The microbial diversity index is shown in Table 3. Microbial diversity PCoA principal coordinate analysis based on 16S and ITS amplicons: and clustering samples in different fermentation periods of front buffer, middle buffer and rear buffer by using R language, so as to determine the composition characteristics of bacteria and fungi in each stage.
Microbial differential analysis based on LEfSe: firstly, verifying species with obvious abundance differences in Daqu at different stages by using a nonparametric Kruskal-Wallis rank sum test, then, using Wilcoxon to test the difference consistency of different species at different stages in the last step, and finally, estimating the influence of the abundance of each species on the difference effect by adopting linear regression analysis. Thus, a characteristic species, i.e. a boom, with significant differences in abundance at each stage of Daqu fermentation was found.
As can be seen from the results of FIG. 2, the composition of the microorganisms in the different fermentation stages has a remarkable difference, and further by linear discriminant analysis, as shown in FIG. 3, a characteristic microbiome (rhizopus, weissella, lactococcus, in the early slow stage, thermoascus, escherichia, streptomyces, bacillus, thermophilic fungi, acinetobacter, etc.) can be found in each stage of Daqu fermentation (LDA value > 2).
Step four: analysis based on flavor OPLS-DA (orthogonal partial least squares discriminant):
the 70 flavor components in the fermentation process of the strong aromatic Daqu are clustered and subjected to orthogonal partial least squares discriminant analysis by using simca software, so that samples in different fermentation periods of front slow, middle stile and rear slow fall are subjected to stage division, characteristic flavor components of each stage are found, obvious differences exist between the flavor components in the stages of front slow, middle stile and rear slow fall of the fermentation process of the Daqu, the flavor components and the content can be subjected to cluster analysis according to the three stages of fermentation, and according to the results, the flavor components generated by the Daqu are accumulated continuously, the types are more and more enriched, the concentration is also gradually increased, and particularly the volatile esters and alcohols are the main flavor components in the white spirit. The reason may be that the microbial community structure is stable in the late stages of fermentation, leading to vigorous metabolic activity which is more favorable for the formation and accumulation of flavor metabolites.
Step five: performing correlation analysis on characteristic microorganisms and characteristic flavor substances:
correlation analysis (|ρ| > 0.6) was performed on 15 characteristic microorganisms with characteristic flavors using R and SPSS software and a correlation heat map was drawn. There were 8 bacteria with a significant correlation with the characteristic flavor profile (p < 0.005). Streptomyces abundance has very significant positive correlation with acetaldehyde, octane ethyl ester, (E, e) -2, 4-hexadienoic acid, ethyl enoate, ethanol, phenethyl alcohol and phenethyl alcohol. Furthermore, the abundance of bacillus is only positively correlated with 2, 3-butanediol. However, the abundance of acinetobacter is significantly inversely related to ethanol, ethyl oleate, aminoalcohol, ethyl palmitate and linoleic acid. Notably, saccharopolyspora, streptomyces and thermoactinomycetes have extremely significant positive correlation with ethyl octane, phenethyl alcohol and phenylazetidine. And the abundance of Acinetobacter, aeromonas, flavobacterium and chrysalis are positively correlated with the content of ethanol and ethyl oleate. While 7 fungi are significantly associated with a characteristic flavor profile. In particular rhizobia, it has a significant positive correlation with 12 characteristic flavours of isoamyl alcohol, amyl acetate, phenylacetaldehyde, nonylactopropyl, 2-n-pentylurea, benzaldehyde, isovaleraldehyde, phenethyl alcohol, etc. There are 7 fungi that are significantly associated with characteristic flavors (p < 0.005): rhizopus is obviously positively correlated with 12 characteristic flavor substances in total, namely isoamyl alcohol, amyl acetate, phenylacetaldehyde, nonolactone propyl, 2-n-pentylurea, benzaldehyde, isovaleraldehyde, phenethyl alcohol, 2, 3-butanediol, trans-2, 4-decadienal, 2-methylnaphthalene and ethyl palmitate; aspergillus has a significant positive correlation with ethyl linoleate; the abundance of the thermoascus is obviously positively correlated with the content of ethanol, ethyl oleate and ethyl valerate; the abundance of thermophilic fungi is obviously positively correlated with the content of ethanol, ethyl oleate, ethyl octanoate and N-amidoalcohol; the abundance of candida is extremely obviously and inversely correlated with the content of 2-n-pentylurea, benzaldehyde, isovaleraldehyde, phenethyl alcohol, 2-phenylcrotonaldehyde and benzyl alcohol; the abundance of the new candida species is simultaneously and remarkably and negatively correlated with the content of isoamyl acetate, 3-hydroxy-2 butanone, isoamyl alcohol, amyl acetate, phenylacetaldehyde, acrylyl phosphite, 2-N-starch furan, benzaldehyde and isoamyl alcohol; the abundance of the genus Celastrus is also extremely significantly inversely correlated with the amount of 2-N-starch furan, benzaldehyde, isoamyl alcohol, phenethyl alcohol, benzyl alcohol, 2,3 butanediol, acetic acid, ethyl acetate, ethyl palmitate. These analyses can help us overall grasp the correlation of characteristic microorganisms with flavour substances at each stage of the fermentation process of Daqu.
Correlation network analysis: the Gephi software is used for carrying out correlation network analysis on characteristic microorganisms and characteristic flavor substances with extremely obvious correlation, and can explain the characteristic bacteria, fungi and dynamic changes of the characteristic flavor substances in each fermentation stage, so that a novel distinguishing method of the characteristic microorganisms in the aroma type Daqu stage based on the microorganisms and the flavor substances is established.
The samples were tested for volatile substances and the data were subjected to statistical analysis and processing as described above, and the results showed that certain volatile content changes (Table 2) were highly consistent with the microbial abundance changes (Table 3), such as the measured changes in 2, 3-butanediol, phenethyl alcohol were substantially consistent with the Bacillus changes, and acetaldehyde and ethyl octane ester were highly consistent with the Streptomyces changes. The benzaldehyde content changes are consistent with the candida abundance changes, and the results completely accord with the conclusion of the method.
TABLE 1 thermal Ji Daqu volatile and organic acid content
TABLE 2 first ten bacteria of the genus Thermo Ji Daqu abundance
TABLE 3 first ten fungi in abundance of heat Ji Daqu
Example 2: cold season fermented Daqu for Sichuan certain winery
A method for monitoring microbial growth metabolism in a process of preparing strong-flavor Daqu, which is operated in the same way as in example 1, and is characterized in that:
collecting a strong fragrance type Daqu sample: samples are taken from a starter making workshop of a well-known winery in Sichuan, daqu samples are taken from four vertexes and the center position of a starter room from top to bottom, fully crushed and uniformly mixed, sampling time points are set to be 0, 6, 16 and 29d according to the process characteristics of starter making (front slow, middle stile and rear slow drop), four groups of parallel samples are made at each time point, and the temperature parameter change in the starter making process is shown in figure 2.
Detecting the flavor substances: the dynamic change of the organic acid in the fermentation process of the Daqu is respectively measured by utilizing a high performance liquid chromatography technology, and the quantification is carried out by a peak area external standard method. And (3) analyzing the change of volatile flavor substances of the Daqu samples in different fermentation periods by using a headspace solid-phase microextraction-gas mass spectrometry (GC-MS), comparing the obtained volatile components with a NIST library for analysis, determining the types of the volatile components with the matching degree of >80, and quantifying by an internal standard method. The changes in the types and contents of the flavoring substances are shown in Table 1, and the types and contents of the organic acids are shown in Table 2.
Microbial diversity: the total DNA of the sample is extracted by adopting a modified CTAB extraction method, and the high-throughput sequencing is carried out by using an Illumina Miseq platform. The microbial diversity index is shown in Table 3.
1. By high throughput sequencing, it was found that the bacteria genus is rhizopus genus in the early slow phase, thermoascus genus in the middle-setting phase, bacillus genus, thermophilic fungi genus, etc. (LDA value > 2).
2. The results of the statistical analysis and treatment of the data show that the content change of certain volatile substances (table 2) is highly consistent with the abundance change of microorganisms (tables 4 and 5), such as the content change of the measured ethanol and acetaldehyde is highly consistent with the abundance change of streptomyces, and the abundance change of benzaldehyde, isovaleraldehyde and candida are highly consistent, and the results completely accord with the conclusion of the method.
TABLE 4 first ten bacterial genera in cold season Daqu abundance
TABLE 5 first ten fungi in abundance of Daqu in cold season
Comparative example 1:
after metabolite detection and high throughput sequencing of the same batch of samples, the following three analysis methods were used to analyze the data:
(1) Directly performing a correlation analysis of the flavour substances with the microorganisms (table 6);
(2) Performing differential cluster analysis on microorganisms, and performing correlation analysis on the microorganisms and flavor substances;
(3) The amount of data on the correlation results between microorganisms and the differential flavor is large and insufficient accuracy and lack of stability was found during the validation process.
Table 6 microbial and flavor correlation
After the analysis method is further optimized and the difference analysis is carried out on the microorganisms and the flavor substances, the correlation analysis is carried out according to the difference analysis result, and the result shows that the accuracy and the universality are obviously improved.
The above examples are given for clarity of illustration only and are not limiting of the embodiments. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. While still being apparent from variations or modifications that may be made by those skilled in the art are within the scope of the invention.
Claims (8)
1. A method for monitoring microbial growth metabolism in a strong-flavor Daqu starter propagation process is characterized by comprising the following steps of: the method comprises the following steps:
step one: samples were collected and the underlying data was tested: collecting Daqu samples in different time in the fermentation process of Daqu at different positions of a fermentation starter room, and respectively measuring flavor substance components and bacteria and fungus structural data of the collected samples to obtain dynamic change results;
step two: microbial diversity PCoA principal coordinate analysis based on 16S and ITS amplicons: clustering samples in different fermentation periods of front slow, middle stile and rear slow by using R language, so as to determine the composition characteristics of bacteria and fungi in each stage;
step three: microbial differential analysis based on LEfSe: firstly, verifying species with obvious abundance differences in Daqu at different stages by using a nonparametric Kruskal-Wallis rank sum test, then, checking the difference consistency of different species at different stages by using Wilcoxon, and finally, estimating the influence of the abundance of each species on the difference effect by adopting linear regression analysis; thus finding out characteristic species with significant differences in abundance at each stage of Daqu fermentation, namely, a boom;
step four: clustering characteristic flavor substances at each stage of front slow, middle stile and rear slow falling: performing cluster analysis on the stages of slow front, middle stile and slow rear falling of the strong aromatic Daqu based on the detected flavor substance components by using simca software, and performing supervised orthogonal partial least squares discriminant analysis on the flavor substances to obtain characteristic flavor substances of each fermentation stage;
step five: performing correlation analysis on characteristic microorganisms and characteristic flavor substances: the spss software is used for carrying out correlation analysis based on the Spilman coefficient on characteristic microorganisms and characteristic flavor substances in each stage of front buffer, middle stile and rear buffer drop, and carrying out double-tail inspection; drawing a correlation cluster heat map by using R language, and further displaying the correlation between the R language and the R language in the process of fermenting the strong aromatic Daqu; screening characteristic microorganisms and characteristic flavor substances with extremely obvious correlation, and drawing a correlation network diagram by using Gephi software; finding out flavor substances which are extremely obviously related to characteristic microorganisms in each stage of front, middle and rear slow falling by combining network analysis results, and determining the content of the characteristic microorganisms extremely obviously related to the characteristic flavor substances by detecting the content of the characteristic flavor substances in actual production, so as to establish a judging method of the growth and metabolism of the characteristic microorganisms in the stage of the aroma type Daqu starter making process; the specific steps of the second step are that R language and Galaxy are used for respectively carrying out cluster analysis and linear discriminant analysis on microorganisms in the process of fermenting the strong aroma type Daqu, so that the clustering analysis is carried out on the microorganisms in each fermentation stage, the place with obvious difference in the compositions of the microorganisms in different fermentation stages is found from the results, the characteristic microorganisms in each fermentation stage of the Daqu can be found through the linear discriminant analysis, the earlier slow stage is rhizopus, streptomyces, aspergillus, saccharopolyspora, candida and candida, the new candida, the middle-stile stage is thermoascus, thermoactinomyces, aeromonas, flavobacterium and cromet Peng Site, and the later slow-release stage is bacillus, thermophilic fungi, acinetobacter and hyposporium.
2. A method for monitoring microbial growth metabolism in a process of making a strong aromatic Daqu as claimed in claim 1, wherein: in the first step, sampling time of the Daqu sample is respectively taken as 0d, 6d, 16d and 29d from the start of starter propagation, and four groups of parallel samples are made at each time point; the sampling positions are four vertexes of the yeast room, and the yeast samples are taken from top to bottom from the center position, and the total is 16 yeast samples.
3. A method for monitoring microbial growth metabolism in a process of making a strong aromatic Daqu as claimed in claim 1, wherein: the flavor substances in the first step comprise organic acid and volatile flavor substances;
the detection method comprises the steps of respectively measuring dynamic changes of organic acid in the fermentation process of Daqu by using a high performance liquid chromatography technology, and quantifying by using a peak area external standard method; and (3) analyzing the change of volatile flavor substances of the Daqu samples in different fermentation periods by using a headspace solid-phase microextraction-gas mass spectrometry combined technology, comparing the obtained volatile components with a NIST library for analysis, determining the types of the volatile components with the matching degree of >80, and quantifying the types by an internal standard method.
4. A method for monitoring microbial growth metabolism in a process of making a strong aromatic Daqu as claimed in claim 1, wherein: the bacterial genus structure data in the first step refers to extracting total DNA of a sample by adopting a modified CTAB extraction method, and carrying out high-throughput sequencing by using an Illumina Miseq platform to obtain various microbial diversity indexes.
5. A method for monitoring microbial growth metabolism in a process of making a strong aromatic Daqu as claimed in claim 1, wherein: the specific steps of the fourth step are that R and SPSS software are used for carrying out correlation analysis on 15 characteristic microorganisms and characteristic flavor substances, rho is 0.6, and a correlation heat map is drawn;
there are 8 bacteria with significant correlation to characteristic flavors, p <0.005:
the abundance of streptomycete has very obvious positive correlation with acetaldehyde, octane ethyl ester, (E, e) -2, 4-hexadienoic acid, ethyl enoate, ethanol, phenethyl alcohol and phenethyl alcohol; the abundance of bacillus is only positively correlated with 2, 3-butanediol; the abundance of acinetobacter is significantly inversely related to ethanol, ethyl oleate, aminoalcohol, ethyl palmitate and linoleic acid; the saccharopolyspora, the crohn Peng Site genus and the thermoactinomycetes have extremely obvious positive correlation with ethyl octanate, phenethyl alcohol and phenylazetidine simultaneously; the abundance of aeromonas and flavobacterium is positively correlated with the content of ethanol and ethyl oleate;
there are 7 fungi that are significantly associated with characteristic flavors:
rhizopus is obviously positively correlated with 12 characteristic flavor substances in total, namely isoamyl alcohol, amyl acetate, phenylacetaldehyde, nonolactone propyl, 2-n-pentylurea, benzaldehyde, isovaleraldehyde, phenethyl alcohol, 2, 3-butanediol, trans-2, 4-decadienal, 2-methylnaphthalene and ethyl palmitate; aspergillus has a significant positive correlation with ethyl linoleate; the abundance of the thermoascus is obviously positively correlated with the content of ethanol, ethyl oleate and ethyl valerate; the abundance of thermophilic fungi is obviously positively correlated with the content of ethanol, ethyl oleate, ethyl octanoate and N-amidoalcohol; the abundance of candida is simultaneously and remarkably inversely related to the content of 2-n-pentylurea, benzaldehyde, isovaleraldehyde, phenethyl alcohol, 2-phenylcrotonaldehyde and benzyl alcohol; the abundance of the new candida species is simultaneously and remarkably and negatively correlated with the content of isoamyl acetate, 3-hydroxy-2 butanone, isoamyl alcohol, amyl acetate, phenylacetaldehyde, acrylyl phosphite, 2-N-starch furan, benzaldehyde and isoamyl alcohol; the abundance of the genus Celastrus is also extremely significantly inversely correlated with the amount of 2-N-starch furan, benzaldehyde, isoamyl alcohol, phenethyl alcohol, benzyl alcohol, 2,3 butanediol, acetic acid, ethyl acetate, ethyl palmitate.
6. A method for monitoring microbial growth metabolism in a process of preparing yeast from strong aromatic Daqu as claimed in claim 1,
the method is characterized in that: the abundance of candida is simultaneously and remarkably inversely related to the content of 2-n-pentylurea, benzaldehyde, isovaleraldehyde, phenethyl alcohol, 2-phenylcrotonaldehyde and benzyl alcohol; meanwhile, the abundance of thermoascus and thermophilic bacteria is obviously positively correlated with the content of ethanol and ethyl oleate.
7. The method for monitoring microbial growth metabolism in the process of preparing the strong aromatic Daqu as claimed in claim 1, wherein the specific steps of the fifth step are as follows: and (3) carrying out correlation network analysis on the characteristic microorganisms and the characteristic flavor substances with extremely obvious correlation in the step four, and explaining the characteristic bacteria, fungi and dynamic changes of the characteristic flavor substances in each fermentation stage, so as to establish a novel distinguishing method of the strong aroma type Daqu stage characteristic microorganisms based on the microorganisms and the flavor substances, and realize stage controllable fermentation.
8. Use of a method for monitoring microbial growth metabolism during the preparation of a concentrated yeast according to any one of claims 1 to 7, characterized in that: the change condition of characteristic flavor substances in each fermentation stage is detected to reflect the actual growth condition of characteristic microorganisms in each stage of the strong-flavor Daqu fermentation so as to make process adjustment in time, and the product quality is ensured by stage controllable fermentation.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017037058A1 (en) * | 2015-08-31 | 2017-03-09 | Chr. Hansen A/S | Lactobacillus fermentum bacteria reducing the concentration of acetaldehyde |
| CN110669630A (en) * | 2019-09-10 | 2020-01-10 | 四川轻化工大学 | Method for judging staged characteristics of fermentation of Sichuan bran vinegar |
| CN112595786A (en) * | 2020-11-25 | 2021-04-02 | 宜宾五粮液股份有限公司 | Quantitative detection method for volatile flavor substances in fermented grains |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017037058A1 (en) * | 2015-08-31 | 2017-03-09 | Chr. Hansen A/S | Lactobacillus fermentum bacteria reducing the concentration of acetaldehyde |
| CN110669630A (en) * | 2019-09-10 | 2020-01-10 | 四川轻化工大学 | Method for judging staged characteristics of fermentation of Sichuan bran vinegar |
| CN112595786A (en) * | 2020-11-25 | 2021-04-02 | 宜宾五粮液股份有限公司 | Quantitative detection method for volatile flavor substances in fermented grains |
Non-Patent Citations (7)
| Title |
|---|
| biotechnology in flavor production;Hackin-F;《Biotechnology in flavor production 》;第309-314页 * |
| 不同轮次酱香型酒醅的理化指标及风味物质变化规律研究;张永燕;黄业传;腾刚;吴树坤;廖华桥;黄治国;;宁夏师范学院学报(04);第30-37页 * |
| 传统臭鸡蛋腌制中细菌区系变化及挥发性风味物质分析;谷新晰;卢海强;申畅;陈伟;檀建新;;中国食品学报(09);第302-309页 * |
| 浓香型大曲储藏过程中细菌菌群差异性分析;施思;彭智辅;乔宗伟;刘多涛;罗青春;涂福明;;食品工业科技(第18期);第157-165页 * |
| 老白干香型白酒制曲过程中微生物多样性及其与风味成分的关系;马冰涛;范恩帝;李泽霞;张煜行;张志民;郭亚伟;姜东明;陈叶福;肖冬光;郭学武;;食品与发酵工业(16);第7-16页 * |
| 邓子新.《中国酒曲制作技艺研究与应用》.中国轻工业出版社,2019,(第第一版版),第248-252页. * |
| 青稞酒发酵过程中的风味功能微生物及其风味代谢特征解析;刘冲冲;冯声宝;吴群;黄和强;陈占秀;李善文;徐岩;;微生物学通报(01);第158-168页 * |
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