Method for rapidly judging quality of high-temperature yeast for making hard liquor

Abstract

The invention provides a method for rapidly judging the quality of high-temperature yeast for making hard liquor, and belongs to the technical field of liquor making. The method comprises the following steps: (1) selecting high-temperature Daqu with a known quality grade as a known sample, carrying out a derivative reaction on the known sample, and analyzing by adopting high performance liquid chromatography to obtain amino acid content information of the known sample; (2) calculating variable importance projection values based on partial least square discriminant analysis, screening amino acids with variable importance projection values greater than 1 as important amino acids, and constructing a simplified high-temperature Daqu quality discrimination model; and (3) obtaining amino acid content information of to-be-detected high-temperature yeast, selecting the content information of the important amino acids, and judging the quality grade of the to-be-detected high-temperature yeast through the simplified high-temperature yeast quality judgment model. The method is objective, reasonable, scientific, efficient, high in operability and high in accuracy, and objective and scientific evaluation of the quality of the high-temperature yeast for making hard liquor can be achieved.

Description

Technical Field

[0001] The invention belongs to the technical field of wine making, and in particular relates to a method for quickly judging the quality of high-temperature Daqu. Background Art

[0002] Maotai-flavor liquor is famous at home and abroad for its unique flavor and occupies an important position in my country's liquor market. Its brewing process mainly includes high-temperature Daqu production and base liquor production. High-temperature Daqu is not only the main source of abundant enzymes and microorganisms in the brewing process of Maotai-flavor liquor, but also provides various raw materials and flavor compounds. Therefore, high-temperature Daqu production is a key link in the brewing of Maotai-flavor liquor, which greatly affects the quality of base liquor. Unlike base liquor, which has clear evaluation standards, high-temperature Daqu still lacks scientific and comprehensive evaluation and grading standards. At present, the evaluation of Daqu quality mainly relies on sensory evaluation, supplemented by the determination of physical and chemical indicators such as moisture content, saccharification power and fermentation power. These evaluation methods, especially sensory evaluation, are relatively subjective and rely on the experience of the evaluator, making it difficult to scientifically characterize the quality of Daqu.

[0003] There are significant differences in the content of microbial communities and flavor substances in high-temperature Daqu of different qualities. Therefore, microbial communities and flavor substances may be two factors that objectively determine the quality of high-temperature Daqu. At present, compared with traditional reliance on culture technology, modern sequencing technology is an effective means to study fermentation microbial communities, which has greatly accelerated the process of studying Daqu microbial communities. Even so, microbial detection still takes a long time, and there is a certain lag in using microbial communities to evaluate the quality of Daqu, making it difficult to quickly determine the quality of Daqu, and thus difficult to meet the large-scale quality identification of Daqu required by wine companies, affecting production efficiency. In addition, compared with other types of Daqu, high-temperature Daqu has the largest proportion of investment in the brewing of Maotai-flavor liquor, usually 90%-110% of the raw grain. Therefore, the impact of flavor compounds on the quality of high-temperature Daqu may be greater than that of microbial communities.

[0004] During the koji making process, the protein in the Daqu raw material is degraded into small molecular weight amino acids. Amino acids are not only a non-volatile flavor substance of Daqu and an important precursor of other flavor substances such as higher alcohols and pyrazines, but also a nitrogen-containing nutrient that provides essential nutrients for the growth and metabolism of liquor brewing microorganisms. As the brewing raw material of Maotai-flavor liquor, the significant difference in Daqu amino acids will inevitably affect whether Daqu can effectively function in liquor brewing.

[0005] The Chinese invention patent with the patent number of 202410490517.7 and the patent name of "Daqu type judgment model, its construction method and Daqu category judgment method" provides a method for judging the type of Daqu based on the Maillard information of Daqu combined with orthogonal partial least squares OPLS-LA discriminant analysis. However, this method is mainly used to distinguish the types of high-temperature Daqu, that is, to distinguish the types of black qu, yellow qu and white qu, and to obtain Maillard information based on amino acid analyzer and gas chromatography-mass spectrometry GC-MS instrument. Data processing and operation are cumbersome and costly. In addition, the accuracy of the information on Daqu flavor substances obtained by the internal standard method is not high. Summary of the invention The present invention provides a method for quickly distinguishing the quality of high-temperature Daqu. A simplified Daqu quality distinction model based on important amino acids is constructed by principal component analysis. The method has short detection time, high timeliness, high accuracy and low cost.

[0006] The present invention provides a method for quickly judging the quality of high-temperature Daqu, comprising the following steps: (1) Selecting high-temperature Daqu of known quality grade as a known sample, performing a derivatization reaction on the known sample, and then using high performance liquid chromatography to analyze the known sample to obtain the amino acid content information of the known sample; (2) The variable importance projection value was calculated based on partial least squares discriminant analysis, and the amino acids with variable importance projection values ​​greater than 1 were screened as important amino acids. Based on the important amino acids, a simplified high-temperature Daqu quality discrimination model was constructed; (3) The same amino acid content information acquisition method as step (1) is used to obtain the amino acid content information of the high-temperature Daqu to be tested, and the content information of the above-mentioned important amino acids is selected therefrom. The quality grade of the high-temperature Daqu to be tested is determined by the above-mentioned simplified high-temperature Daqu quality discrimination model. Furthermore, in step (1), the derivatization reaction of the known sample includes: mixing the Daqu sample extract, sodium bicarbonate solution, derivatization agent solution, and phosphate buffer in a dosage ratio of 200 μL:450 μL:450 μL:900 μL, and performing a heat-insulating reaction in the dark.

[0007] Furthermore, in step (1), the preparation process of the Daqu sample extract comprises: crushing the high-temperature Daqu into powder, uniformly mixing with a hydrochloric acid solution at a dosage ratio of 3g:20-30mL, ultrasonically treating at 250W for 30 minutes, and then centrifuging at 7000-8000r / min for 10 minutes, and taking the supernatant as the Daqu sample extract; In step (1), the preparation process of the derivatizing agent solution comprises: dissolving 2,4-dinitrofluorobenzene in acetonitrile according to a dosage ratio of 0.1~2mL:100mL to obtain a derivatizing agent solution.

[0008] Furthermore, in step (1), the preparation process of the phosphate buffer comprises: uniformly mixing sodium hydroxide solution, potassium dihydrogen phosphate solution, and distilled water in a dosage ratio of 70-80 mL: 300 mL: 120-130 mL to obtain a phosphate buffer; In step (1), the preparation process of the sodium bicarbonate solution comprises: dissolving solid sodium bicarbonate in distilled water according to a dosage ratio of 1-6 g:100 mL to obtain a sodium bicarbonate solution.

[0009] Furthermore, in step (1), the temperature of the insulation is 50-70°C, and the reaction time in the dark is 0.5-2 hours. Preferably, the temperature of the insulation is 60°C, and the reaction time in the dark is 1 hour.

[0010] Furthermore, in step (1), the HPLC analysis conditions are as follows: the model of the HPLC instrument is Agilent 1100, the chromatographic column is ZORBAX Eclipse Plus C18 1100 (250 mm× 4.6 mm× 5 μm), the detection wavelength is 360 nm, the column temperature is 40°C, the flow rate is 1.0 mL / min, the injection volume is 10 μL, and the mobile phase is gradient elution.

[0011] Furthermore, in step (1), the mobile phase comprises: mixing solid anhydrous sodium acetate, triethylamine and ultrapure water in a dosage ratio of 3.56 g:10 mL:1000 mL, adjusting the pH to 6.5, and then filtering through a 0.22 μm filter membrane to obtain mobile phase A; mixing acetonitrile and ultrapure water in a volume dosage ratio of 1:1, and then filtering through a 0.22 μm filter membrane to obtain mobile phase B.

[0012] Furthermore, in step (1), the mobile phase gradient elution program is: the initial gradient is 74.2% mobile phase A, maintained for 14 minutes, linearly decreased to 45% mobile phase A at 25 minutes, linearly decreased to 32% mobile phase A and 25% mobile phase A at 32 minutes and 40 minutes, then linearly decreased to 5% mobile phase A at 55 minutes, and finally, the gradient increased to 74.2% mobile phase A at 55 minutes and maintained for 5 minutes. The present invention experimentally verifies that the mobile phase gradient elution method affects the detection effect of each amino acid in the sample, and screens out the best gradient elution method. Furthermore, in step (2), the method for constructing a simplified high-temperature Daqu quality discrimination model is principal component analysis.

[0013] The present invention has the following advantages: The present invention provides a method for rapidly discriminating the quality of high-temperature Daqu based on amino acids, and adopts principal component analysis to construct a simplified Daqu quality discrimination model based on important amino acids, which can rapidly discriminate the quality of high-temperature Daqu and the corresponding Daqu quality grade, is suitable for efficiently processing large quantities, and is applicable to large-scale high-temperature Daqu quality identification by wine companies, with high accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0015] Figure 1 This is a diagram showing the effects of different derivatization reaction treatment methods on the high performance liquid chromatography detection of amino acids in samples according to Example 1 of the present invention; Figure 2 , Figure 3 and Figure 4 The figure is the effect of different mobile phase gradient elution methods on the detection of amino acids in samples by high performance liquid chromatography in Example 1 of the present invention, wherein A, B, C, D, E, and F represent the peak graphs of group 1, group 2, group 3, group 4, group 5, and group 6, respectively; Figure 5 This is a comparison chart of total amino acid content of high-temperature Daqu of different quality grades in Example 2 of the present invention; Figure 6 This is a discriminant model diagram of high-temperature Daqu of different quality grades based on 20 kinds of amino acids in Example 2 of the present invention; wherein A-superior high-temperature Daqu, B-first-grade high-temperature Daqu; Figure 7 This is a waterfall diagram of the amino acid VIP of Daqu calculated based on PLS-DA in Example 2 of the present invention; Figure 8 This is a discriminant diagram of high-temperature Daqu of different quality grades based on six important amino acids in Example 2 of the present invention; Fig. 9 Schematic diagram of the placement of gauze bags in pile fermentation and cellar fermentation in Example 3 of the present invention; Fig.10 The effect of the six amino acids in Example 3 of the present invention on the ethyl acetate content in the brewing process of Maotai-flavor liquor; Fig.11 This is the effect of the six amino acids in Example 3 of the present invention on the content of n-propanol in the brewing process of Maotai-flavor liquor. DETAILED DESCRIPTION

[0016] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. In the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other.

[0017] The main function of high-temperature Daqu is to be used as a flavoring agent and fermentation agent in the brewing of Maotai-flavor liquor. High-temperature Daqu that can better play its role in the brewing process and brew high-quality liquor can be called high-quality Daqu. Amino acids, as a nitrogen-containing nutrient, are essential for the growth and metabolism of microorganisms. They are also important non-volatile flavor compounds in Daqu, especially high-temperature Daqu, and important precursors of certain flavor substances such as higher alcohols and pyrazines. Exploring the effect of amino acids on flavor formation in the brewing process of Maotai-flavor liquor is an effective method.

[0018] The embodiment of the present invention provides a method for quickly judging the quality of high-temperature Daqu, comprising the following steps: (1) Selecting high-temperature Daqu of known quality grade as a known sample, performing a derivatization reaction on the known sample, and then using high performance liquid chromatography to analyze the known sample to obtain the amino acid content information of the known sample; (2) The variable importance projection value (VIP) was calculated based on partial least squares discriminant analysis (PLS-DA), and amino acids with variable importance projection values ​​greater than 1 were screened as important amino acids. Based on the important amino acids, a simplified high-temperature Daqu quality discrimination model was constructed; (3) The same amino acid content information acquisition method as step (1) is used to obtain the amino acid content information of the high-temperature Daqu to be tested, and the content information of the above-mentioned important amino acids is selected therefrom. The quality grade of the high-temperature Daqu to be tested is determined by the above-mentioned simplified high-temperature Daqu quality discrimination model. The present invention provides a method for quickly distinguishing the quality of high-temperature Daqu. High performance liquid chromatography is used to obtain the amino acid content information in high-temperature Daqu of different quality grades. In combination with the principal component analysis (PCA) method, a model based on the important amino acid content and the Daqu quality grade discrimination is constructed, thereby realizing the discrimination of the high-temperature Daqu quality grade.

[0019] The present invention proposes for the first time to incorporate amino acids into the quality grading and evaluation system of Daqu, enriching the quality evaluation indicators of Daqu. The method of detecting amino acids in Daqu by high performance liquid chromatography was optimized, and the optimal detection conditions were obtained. It also verified the influence of amino acids on the formation of flavor substances in the brewing process of Maotai-flavor liquor, and clarified that the difference in amino acids in Daqu has a significant impact on the function of high-temperature Daqu in the brewing process of Maotai-flavor liquor. The method is objective and reasonable, scientific and efficient, highly operational, and highly accurate. It can achieve an objective and scientific evaluation of the quality of high-temperature Daqu, and provides process theoretical parameters for building an objective and comprehensive Daqu quality rating system. In one embodiment of the present invention, in step (1), the derivatization reaction of the known sample includes: mixing the Daqu sample extract, sodium bicarbonate solution, derivatization agent solution, and phosphate buffer in a dosage ratio of 200 μL:450 μL:450 μL:900 μL, and performing a heat-insulating reaction in the dark.

[0020] In one embodiment of the present invention, in step (1), the preparation process of the Daqu sample extract comprises: crushing the high-temperature Daqu into powder, uniformly mixing it with a hydrochloric acid solution at a dosage ratio of 3g:20-30mL, ultrasonically treating it at 250W for 30 min, and then centrifuging it at 7000-8000r / min for 10 min, and taking the supernatant as the Daqu sample extract.

[0021] Preferably, the preparation process of the hydrochloric acid solution is as follows: concentrated hydrochloric acid is dissolved in distilled water in a dosage ratio of 8.3 mL:100 mL to obtain the hydrochloric acid solution. In one embodiment of the present invention, in step (1), the preparation process of the derivatizing agent solution comprises: dissolving 2,4-dinitrofluorobenzene in acetonitrile at a ratio of 0.1-2 mL:100 mL to obtain a derivatizing agent solution. Preferably, dissolving 2,4-dinitrofluorobenzene in acetonitrile at a ratio of 1 mL:100 mL to obtain a derivatizing agent solution.

[0022] In one embodiment of the present invention, in step (1), the preparation process of the sodium bicarbonate solution comprises: dissolving solid sodium bicarbonate in distilled water at a dosage ratio of 1-6 g:100 mL to obtain a sodium bicarbonate solution. Preferably, dissolving solid sodium bicarbonate in distilled water at a dosage ratio of 4.2 g:100 mL to obtain a sodium bicarbonate solution.

[0023] In one embodiment of the present invention, in step (1), the preparation process of the phosphate buffer comprises: mixing sodium hydroxide solution, potassium dihydrogen phosphate solution, and distilled water in a dosage ratio of 70-80 mL: 300 mL: 120-130 mL to obtain a phosphate buffer. Preferably, sodium hydroxide solution, potassium dihydrogen phosphate solution, and distilled water in a dosage ratio of 72.50 mL: 300 mL: 127.5 mL are mixed to obtain a phosphate buffer.

[0024] More preferably, the preparation process of the sodium hydroxide solution comprises: dissolving solid sodium hydroxide in distilled water according to a dosage ratio of 0.4 g:100 mL to obtain the sodium hydroxide solution.

[0025] More preferably, the preparation process of the potassium dihydrogen phosphate solution comprises: dissolving solid potassium dihydrogen phosphate in distilled water at a dosage ratio of 1.7 g:300 mL to obtain the potassium dihydrogen phosphate solution. In one embodiment of the present invention, in step (1), the temperature of the insulation is 50-70°C, and the time of the light-proof reaction is 0.5-2 hours. Preferably, the temperature of the insulation is 60°C, and the light-proof reaction time is 1 hour.

[0026] In one embodiment of the present invention, in step (1), the high performance liquid chromatography analysis conditions are: the model of the high performance liquid chromatograph is Agilent 1100, the chromatographic column is ZORBAX Eclipse Plus C18 1100 (250 mm× 4.6 mm× 5μm), the detection wavelength is 360 nm, the column temperature is 40°C, the flow rate is 1.0 mL / min, the injection volume is 10 μL, and the mobile phase is gradient elution. It should be noted that Agilent 1100 is a high performance liquid chromatograph (HPLC) developed by Agilent, 250 ×4.6 mm represents the length and inner diameter of the chromatographic column, the units are millimeters (mm) and millimeters (mm), respectively, and 5 represents the particle size of the chromatographic column filler, the unit is micrometer (μm).

[0027] In one embodiment of the present invention, in step (1), the mobile phase comprises: solid anhydrous sodium acetate, triethylamine and ultrapure water are mixed evenly in a dosage ratio of 3.56 g:10 mL:1000 mL, the pH is adjusted to 6.5, and then filtered through a 0.22 μm filter membrane to obtain mobile phase A; acetonitrile and ultrapure water are mixed evenly in a volume dosage ratio of 1:1, and then filtered through a 0.22 μm filter membrane to obtain mobile phase B.

[0028] In one embodiment of the present invention, in step (1), the mobile phase gradient elution program is: the initial gradient is 74.2% mobile phase A, maintained for 14 minutes, linearly decreased to 45% mobile phase A at 25 minutes, linearly decreased to 32% mobile phase A and 25% mobile phase A at 32 minutes and 40 minutes, then linearly decreased to 5% mobile phase A at 55 minutes, and finally, the gradient increased to 74.2% mobile phase A at 55 minutes and maintained for 5 minutes. The present invention experimentally verifies that the mobile phase gradient elution method affects the detection effect of each amino acid in the sample, and screens out the best gradient elution method. In one embodiment of the present invention, in step (1), the amino acids are quantified using an external standard method.

[0029] In a preferred embodiment of the present invention, in step (1), the types of amino acids detected by high performance liquid chromatography may include histidine, proline, tryptophan, glutamine, alanine, glutamic acid, valine, aspartic acid, phenylalanine, lysine, serine, leucine, tyrosine, glycine, threonine, methionine, asparagine, cysteine, arginine, and isoleucine.

[0030] In one embodiment of the present invention, in step (1), the high-temperature Daqu of known quality grade is classified according to the grade of the sample. For example, the Daqu samples of known quality grade can be divided into superior high-temperature Daqu, first-grade high-temperature Daqu, and In one embodiment of the present invention, in step (2), the method for constructing a simplified high-temperature Daqu quality discrimination model is principal component analysis (PCA). Principal component analysis (PCA) is a multivariate statistical technique, the main principle of which is to project high-dimensional data into a lower-dimensional space, by converting multiple variables in the original data into a set of new, unrelated variables (called principal components), and using the new variables to display the characteristics of the data in a smaller dimension, which can be used to compare the differences between samples.

[0031] In an embodiment of the present invention, variable importance in projection (VIP) is an indicator used to measure the importance of a variable in a partial least squares regression (PLS) analysis. In the context of PLS ​​regression, the VIP index is widely used to highlight the relative importance of a given variable in predicting a response. Variables with a VIP value greater than 1 are considered to be particularly important to the model.

[0032] In a preferred embodiment of the present invention, in step (2), when the variable importance projection value is greater than 1, the obtained important amino acids may include arginine, glutamine, proline, lysine, tryptophan and glutamate.

[0033] The present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0034] Example 1 Optimization of HPLC method for detecting amino acid content in Daqu 1. Experimental Materials and Equipment 1. Experimental materials and reagents Daqu was selected from the finished product library of Guizhou Guotai Digital Wine Group Co., Ltd. Amino acid standards, concentrated hydrochloric acid, sodium hydroxide, potassium dihydrogen phosphate, sodium bicarbonate, 2,4-dinitrofluorobenzene, sodium acetate, glacial acetic acid, and triethylamine were purchased from Shanghai Aladdin Biochemical Technology Co., Ltd., and acetonitrile was purchased from Merck, Germany.

[0035] 2. Reagent preparation (1) Preparation of hydrochloric acid solution: Accurately measure 8.3 mL of concentrated hydrochloric acid, add it to 1000 mL of distilled water, and mix well to obtain a hydrochloric acid solution.

[0036] (2) Preparation of Daqu extract: Crush the Daqu into Daqu powder, accurately weigh 3g±0.02g of Daqu powder, place it in a 50mL centrifuge tube, add 20mL of hydrochloric acid solution, vortex and oscillate, ultrasonicate at 250W for 30 min, then centrifuge at 7000-8000r / min for 10 min, and take the supernatant as the Daqu sample extract.

[0037] (3) Preparation of phosphate buffer (pH 7.0): First, weigh 0.40 g of solid sodium hydroxide and dissolve it in 100 mL of ultrapure water to prepare a sodium hydroxide solution. Secondly, accurately weigh 1.70 g of solid potassium dihydrogen phosphate and dissolve it in 300 mL of ultrapure water to prepare a potassium dihydrogen phosphate solution. Finally, measure 72.50 mL of sodium hydroxide solution and 300 mL of potassium dihydrogen phosphate solution, make up to 500 mL, and mix well to obtain a phosphate buffer.

[0038] (4) Preparation of 0.5 mol / L sodium bicarbonate solution: Accurately weigh 4.20 g of sodium bicarbonate, dissolve it in 100 mL of ultrapure water, and mix well to obtain a sodium bicarbonate solution.

[0039] (5) Preparation of derivatization agent solution: Accurately measure 0.25 mL of 2,4-dinitrofluorobenzene and dissolve it in 25 mL of acetonitrile. Mix well to obtain a derivatizing agent solution.

[0040] (6) Preparation of mobile phase A: Accurately weigh 3.56 g of anhydrous sodium acetate, dissolve it in 1000 mL of ultrapure water, add 10 mL of triethylamine, adjust the pH to 6.50 with glacial acetic acid, and filter with a 0.22 μm filter membrane before use to obtain mobile phase A.

[0041] (7) Preparation of mobile phase B: Acetonitrile and ultrapure water were mixed evenly in a volume ratio of 1:1 and filtered with a 0.22 μm filter membrane before use to obtain mobile phase B.

[0042] 3. Main instruments and equipment Agilent 1100 high performance liquid chromatograph (Agilent Technologies, Inc., USA); chromatographic column: ZORBAX Eclipse Plus C18 1100 (250×4.6mm×5) (Agilent Technologies, Inc., USA); MS204S electronic balance (Mettler-Toledo Instrument Co., Ltd.); PHS-SBW ultrasonic cleaner (Kunshan Ultrasonic Instrument Co., Ltd.); 5408 desktop centrifuge (Shanghai Anting Science and Technology Instrument Factory).

[0043] 2. Experimental Methods 2.1 Sample pre-column derivatization optimization experiment Before testing the amino acid content in the sample, the sample must be subjected to a pre-column derivatization experiment, which directly affects the detection effect of the sample amino acid. The same high-temperature Daqu sample was divided into 4 groups and numbered. The solution dosage ratio in the derivatization reaction system was different. The specific treatment methods are shown in Table 1. The detection effect of Daqu amino acids by different derivatization reaction treatment methods is shown in Table 1. Figure 1 The analysis results of the four groups of samples were compared. The results showed that as the ratio of the derivatizing agent increased, the peak area of ​​the amino acid increased. However, if the ratio was too high, other impurity peaks would be generated. The detection effect of the target substance in the sample was best when the ratio of sample extract: sodium bicarbonate solution: derivatizing agent: phosphate buffer solution in the reaction system was 200μL: 450μL: 450μL: 900μL.

[0044] Table 1 Derivatization reaction treatment method

[0045] 2.2 Optimization experiment of HPLC gradient elution method In order to detect multiple amino acids in the sample, the mobile phase gradient elution method is used for detection. The mobile phase gradient elution method directly affects the detection effect of each amino acid in the sample, so it is very important to choose a suitable gradient elution method. The same pre-column derivatized samples were selected to compare the detection effects of six gradient elution methods on the target substances in the samples. The specific methods are shown in Table 2. The detection effects of different mobile phase gradient elution methods on Daqu amino acids are shown in Table 2. Figure 2 , Figure 3 , Figure 4 As shown, A, B, C, D, E, and F represent the detection effect diagrams of Group 1, Group 2, Group 3, Group 4, Group 5, and Group 6, respectively. The amino acid substances in the red box area in the figure have similar retention times, which are easy to overlap and lead to poor detection effects. From the detection effects of different groups, the method of Group 5 is used, and the separation effect of amino acids is the best, and the detection effect is the best. Table 2 Derivatization reaction treatment method

[0046] Example 2 Analysis of amino acid content in Daqu samples of different quality levels and construction of discrimination model 1. Test samples Modeling Daqu samples: superior sauce-flavored high-temperature Daqu (9 samples), first-class sauce-flavored high-temperature Daqu (9 samples); Daqu samples to be tested: superior sauce-flavored high-temperature Daqu (10 samples), first-class sauce-flavored high-temperature Daqu (10 samples); All Daqu samples were taken from the finished product library of Guizhou Guotai Digital Wine Group Co., Ltd. Daqu samples are taken according to the five-point sampling method, and professional workers use their experience to conduct sensory evaluation and grading of the Daqu samples, that is, sensory evaluation is carried out by observing the appearance, cross-section and smell of Daqu. The appearance includes dressing, large surface mycelium color, cracks and smoothness; the cross-section includes the neatness of the cross-section, fullness of mycelium, color, water circle and skin; the smell includes the aroma of the mycelium and foreign tastes, etc. The quality grade of the koji powder Daqu is subjectively evaluated to obtain excellent and first-level high-temperature Daqu samples.

[0047] 2. Determination of amino acid content in Daqu and establishment of discrimination model 2.1 Preparation of Daqu extract The modeled Daqu was crushed into Daqu powder, 3g±0.02g Daqu powder was accurately weighed and placed in a 50mL centrifuge tube, 20mL hydrochloric acid solution was added, vortexed, ultrasonically treated at 250W for 30 min, and then centrifuged at 7000-8000r / min for 10 min. The supernatant was the Daqu sample extract.

[0048] 2.2 Sample derivatization reaction Measure 200 μL of Daqu sample extract, 450 μL of sodium bicarbonate solution, 450 μL of derivatizing agent solution, and 900 μL of phosphate buffer respectively and place them in a 2 mL brown centrifuge tube, mix them evenly, and keep them at 60°C in the dark for 1 h. The preparation process of the Daqu sample extract is as follows: crush the Daqu into Daqu powder, uniformly mix it with the hydrochloric acid solution at a dosage ratio of 3g:20mL, ultrasonically treat it at 250W for 30 minutes, and then centrifuge it at 7830r / min for 10 minutes, and take the supernatant as the Daqu sample extract; the preparation process of the hydrochloric acid solution is as follows: dissolve concentrated hydrochloric acid in distilled water at a dosage ratio of 8.3mL:100mL to obtain the hydrochloric acid solution; The preparation process of the sodium bicarbonate solution is as follows: solid sodium bicarbonate is dissolved in distilled water according to a dosage ratio of 4.2 g:100 mL to obtain a sodium bicarbonate solution; The preparation process of the derivatizing agent solution is as follows: dissolving 2,4-dinitrofluorobenzene in acetonitrile at a dosage ratio of 1 mL:10 mL to obtain the derivatizing agent solution; The preparation process of the phosphate buffer solution is as follows: sodium hydroxide solution, potassium dihydrogen phosphate solution and distilled water are uniformly mixed according to a dosage ratio of 72.50 mL: 300 mL: 127.5 mL to obtain the phosphate buffer solution; wherein, the preparation process of the sodium hydroxide solution is as follows: solid sodium hydroxide is dissolved in distilled water according to a dosage ratio of 0.4 g: 100 mL to obtain the sodium hydroxide solution; the preparation process of the potassium dihydrogen phosphate solution is as follows: solid potassium dihydrogen phosphate is dissolved in distilled water according to a dosage ratio of 1.7 g: 300 mL to obtain the potassium dihydrogen phosphate solution.

[0049] 2.3 Obtaining amino acid content information of samples and constructing a discriminant model The amino acid content in the samples was detected by high performance liquid chromatography. The chromatographic conditions were: Agilent 1100 high performance liquid chromatograph, ZORBAX Eclipse Plus C18 1100 (250 mm×4.6 mm×5 μm), detection wavelength 360 nm, column temperature 40°C, flow rate 1.0 mL / min, injection volume 10 μL, gradient elution program with an initial gradient of 74.2% mobile phase A, maintained for 14 min, linearly decreased to 45% mobile phase A at 25 min, linearly decreased to 32% mobile phase A and 25% mobile phase A at 32 min and 40 min, then linearly decreased to 5% mobile phase A at 55 min, and finally, the gradient increased to 74.2% mobile phase A at 55 min and maintained for 5 min. The retention time index was used to identify the amino acids, and the external standard method was used to quantify the amino acids. The amino acids detected are free amino acids, including histidine, proline, tryptophan, glutamine, alanine, glutamic acid, valine, aspartic acid, phenylalanine, lysine, serine, leucine, tyrosine, glycine, threonine, methionine, asparagine, cysteine, arginine, and isoleucine. Figure 5 As shown, the total amino acid content of high-temperature Daqu with different qualities showed significant differences.

[0050] The principal component analysis (PCA) method was used to construct a discriminant model based on the relationship between the content of the above 20 amino acids and the quality of high-temperature Daqu. The results are as follows: Figure 4 shown. Figure 6 That is the discriminant model diagram of the present invention for different grades of high-temperature Daqu based on the above 20 kinds of amino acid contents, among which A-superior grade high-temperature Daqu, B-first-grade high-temperature Daqu. The discriminant model diagram shows that the total contribution rate of the two principal components is 98.6%, indicating that the model can effectively discriminate the quality grade of high-temperature Daqu.

[0051] 2.4 Screening of important amino acids Considering the large-scale quality discrimination of Daqu in wine companies, building a simple and easy-to-operate quality discrimination model can greatly improve work efficiency. Therefore, the constructed high-temperature Daqu quality discrimination model is simplified, that is, partial least squares discriminant analysis (PLS-DA) is performed based on the "ropls" package using R language to calculate the variable importance projection value (VIP) of the above 20 amino acids of high-temperature Daqu of different qualities. VIP>1 is preferred. P <0.05 was the screening condition to screen important amino acids. Figure 7 This is a waterfall chart of the amino acid VIP of Daqu calculated based on PLS-DA. The figure shows that VIP>1. PThere are six key amino acids with a concentration of less than 0.05, namely arginine, glutamine, proline, lysine, tryptophan and glutamate. 2.5 Using important amino acids to construct a simplified discrimination model PCA was used to discriminate the quality of high-temperature Daqu. The six important amino acids screened above were used as independent variables, and two different qualities of high-temperature Daqu with sauce aroma were used as dependent variables to conduct discriminant analysis and construct a discriminant model for the quality grade of Daqu. Figure 8 This is a discriminant model diagram for different grades of high-temperature Daqu based on the above 6 important amino acid contents in the present invention, in the figure: A-superior high-temperature Daqu, B-first-grade high-temperature Daqu, the discriminant model diagram shows that the total contribution rate of the two principal components is 97.6%, indicating that after simplifying the discriminant model, the high-temperature Daqu quality discriminant model established based on these 6 important amino acids can also effectively discriminate the quality of Daqu.

[0052] 2.6 Determining the quality of high-temperature Daqu and model verification The above-mentioned high-temperature Daqu samples to be tested (including 10 high-grade sauce-flavored high-temperature Daqu samples and 10 first-grade sauce-flavored high-temperature Daqu samples) were selected as the test group, and the high-temperature Daqu was derivatized according to the method described in steps 2.1 to 2.4 above. Then, high-performance liquid chromatography analysis was used to obtain the amino acid content information of the samples to be tested. From the results obtained, the content information of the above-mentioned 6 important amino acids was directly selected, and the discrimination model constructed in step 2.5 was used to discriminate the quality of the high-temperature Daqu and verify the discrimination effect.

[0053] Table 3 shows the verification results. It can be seen from Table 3 that the discrimination accuracy of the discriminant model for the other test sample high-grade high-temperature Daqu is 9 / 10×100%=90%, the discrimination accuracy for the first-grade high-temperature Daqu is 10 / 10×100%=100%, and the comprehensive discrimination accuracy is (9+10) / (10+10)=95%. The identification results show that the model has a good effect on the discrimination of Daqu quality.

[0054] Table 3 shows the test sample verification results

[0055] Note: HQ means high-quality high-temperature Daqu, LQ means first-class high-temperature Daqu Example 3 Verification of amino acids as an important indicator for judging the quality of Daqu According to the above examples, six important differential amino acids were screened. Based on these six amino acids, an in situ fermentation system was used to explore the effects of these six amino acids on the content of flavor substances in the brewing process of Maotai-flavor liquor.

[0056] 1. Experimental Materials and Equipment 1. Experimental materials and reagents Arginine, glutamine, proline, lysine, tryptophan, glutamic acid (Shanghai Aladdin Biochemical Technology Co., Ltd.), acetonitrile (Merck, Germany).

[0057] 2. Main instruments and equipment Agilent 1100 high performance liquid chromatograph (Agilent Technologies, Inc., USA); chromatographic column: ZORBAX Eclipse Plus C18 1100 (250×4.6mm×5) (Agilent Technologies, Inc., USA); MS204S electronic balance (Mettler-Toledo Instrument Co., Ltd.); PHS-SBW ultrasonic cleaner (Kunshan Ultrasonic Instrument Co., Ltd.); 5408 desktop centrifuge (Shanghai Anting Science and Technology Instrument Factory).

[0058] 2. Experimental Methods 2.1 Investigating the effects of six amino acids on the formation of flavor substances during the brewing process of Maotai-flavor liquor In the rough sand round of Maotai-flavor liquor in the wine company, an in-situ fermentation system was used to conduct experiments. The proportion of high-temperature Daqu added was 12%. The experimental group added a single amino acid. The addition amounts of arginine, glutamine, proline, lysine, tryptophan, and glutamic acid were 1000 mg / (kg Daqu), 1000 mg / (kg Daqu), 1000 mg / (kg Daqu), 700 mg / (kg Daqu), 800 mg / (kg Daqu), and 800 mg / (kg Daqu), respectively. No amino acids were added to the control group. The placement positions of the gauze bags in the experimental and control groups are shown in the figure. Fig. 9 After the fermentation in the cellar, a certain amount of mash was taken to test the content of ethyl acetate and n-propanol.

[0059] 2.2 Determination of ethyl acetate and n-propanol content in fermented grains 2.2.1 Distillation of fermented grains Weigh 100±1g of fermented grains, distill them using a distillation device, and take 100mL of distillate for inspection.

[0060] 2.2.2 Detection of volatile flavor substances in distillate The contents of ethyl acetate and n-propanol in the fermented grains distillate were determined by gas chromatography based on the external standard method, and the average value was taken for 3 measurements. Chromatographic conditions: The chromatographic column was DB-WAX (60 m×250 μm×0.25 μm). The detector was a hydrogen flame ionization detector; the carrier gas was high-purity nitrogen; the split ratio was 100:1; the injection port temperature was 300℃; the detector temperature was 250℃; the injection volume was 1μL. The initial temperature was 40℃, maintained for 8 min; it was increased to 90℃ at 5℃ / min, and then increased to 180℃ at 6℃ / min, maintained for 10 min, and each sample was run for 43 min.

[0061] 3. Experimental Results Ethyl acetate is an ester with a high content in Maotai-flavor liquor. It has the fruity aroma of apples and bananas and makes an important contribution to the aroma. n-Propanol is an alcohol substance with a high content in Maotai-flavor liquor. A moderate amount of n-propanol is an indispensable flavor component in liquor. It has the function of presenting aroma and flavor and helping aroma. Excessive amount will make the liquor taste unpleasant and bitter, and increase the discomfort after drinking. In the actual production process of Maotai-flavor liquor, the content of higher alcohols in the first round of base liquor is high, which affects the flavor of the base liquor and the use of blending in the later stage, and is not conducive to improving the comfort after drinking.

[0062] Fig.10 and Fig.11 The effects of six kinds of amino acids on the content of ethyl acetate and n-propanol in the brewing process of Maotai-flavor liquor are shown respectively. As can be seen from the figure, compared with the control group, the addition of amino acids in the brewing process has a significant effect on increasing acetate and reducing n-propanol, which indirectly indicates that high-temperature Daqu with high amino acid content helps to improve the brewing flavor of Maotai-flavor liquor, which is consistent with the result that the amino acid content of high-quality high-temperature Daqu is high. In short, amino acids have an important influence on the function of high-temperature Daqu in the brewing process of Maotai-flavor liquor and are an important substance affecting the quality grade of Daqu.

[0063] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for quickly judging the quality of high-temperature Daqu, characterized in that: The steps include: (1) Selecting high-temperature Daqu of known quality grade as a known sample, performing a derivatization reaction on the known sample, and then using high performance liquid chromatography to analyze the known sample to obtain the amino acid content information of the known sample; (2) The variable importance projection value was calculated based on partial least squares discriminant analysis, and the amino acids with variable importance projection values ​​greater than 1 were screened as important amino acids. Based on the important amino acids, a simplified high-temperature Daqu quality discrimination model was constructed; (3) The same amino acid content information acquisition method as step (1) is used to obtain the amino acid content information of the high-temperature Daqu to be tested, and the content information of the above-mentioned important amino acids is selected therefrom. The quality grade of the high-temperature Daqu to be tested is determined by the above-mentioned simplified high-temperature Daqu quality discrimination model.

2. The method according to claim 1, characterized in that In step (1), the derivatization reaction of the known sample includes: mixing the Daqu sample extract, sodium bicarbonate solution, derivatization agent solution, and phosphate buffer in a dosage ratio of 200 μL:450 μL:450 μL:900 μL, and performing a heat-insulating reaction in the dark.

3. The method according to claim 2, characterized in that In step (1), the preparation process of the Daqu sample extract comprises: crushing the high-temperature Daqu into powder, uniformly mixing with hydrochloric acid solution at a dosage ratio of 3g:20-30mL, ultrasonically treating at 250W for 30 minutes, and then centrifuging at 7000-8000r / min for 10 minutes, and taking the supernatant as the Daqu sample extract; In step (1), the preparation process of the derivatizing agent solution comprises: dissolving 2,4-dinitrofluorobenzene in acetonitrile according to a dosage ratio of 0.1~2mL:100mL to obtain a derivatizing agent solution.

4. The method according to claim 2, characterized in that: In step (1), the preparation process of the phosphate buffer comprises: uniformly mixing a sodium hydroxide solution, a potassium dihydrogen phosphate solution, and distilled water in a dosage ratio of 70-80 mL: 300 mL: 120-130 mL to obtain a phosphate buffer; In step (1), the preparation process of the sodium bicarbonate solution comprises: dissolving solid sodium bicarbonate in distilled water according to a dosage ratio of 1-6 g:100 mL to obtain a sodium bicarbonate solution.

5. The method according to claim 2, characterized in that: In step (1), the temperature of the insulation is 50-70°C, and the reaction time in the dark is 0.5-2 hours. Preferably, the temperature of the insulation is 60°C, and the reaction time in the dark is 1 hour.

6. The method according to claim 1, characterized in that In step (1), the HPLC analysis conditions are as follows: the model of the HPLC instrument is Agilent 1100, the chromatographic column is ZORBAX Eclipse Plus C18 1100 (250 mm× 4.6 mm× 5 μm), the detection wavelength is 360 nm, the column temperature is 40°C, the flow rate is 1.0 mL / min, the injection volume is 10 μL, and the mobile phase is gradient elution.

7. The method according to claim 6, characterized in that In step (1), the mobile phase comprises: mixing solid anhydrous sodium acetate, triethylamine and ultrapure water in a dosage ratio of 3.56 g:10 mL:1000 mL, adjusting the pH to 6.5, and then filtering through a 0.22 μm filter membrane to obtain mobile phase A; mixing acetonitrile and ultrapure water in a volume dosage ratio of 1:1, and then filtering through a 0.22 μm filter membrane to obtain mobile phase B.

8. The method according to claim 6, characterized in that In step (1), the mobile phase gradient elution program is: the initial gradient is 74.2% mobile phase A, maintained for 14 minutes, linearly decreased to 45% mobile phase A at 25 minutes, linearly decreased to 32% mobile phase A and 25% mobile phase A at 32 minutes and 40 minutes, then linearly decreased to 5% mobile phase A at 55 minutes, and finally, the gradient increased to 74.2% mobile phase A at 55 minutes and maintained for 5 minutes. The present invention verifies through experiments that the mobile phase gradient elution method will affect the detection effect of each amino acid in the sample, and screens out the best gradient elution method.

9. The method according to claim 1, characterized in that: In step (2), the method for constructing a simplified high-temperature Daqu quality discrimination model is principal component analysis.

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