CN114965838B - Construction method and identification method of malt processed product identification model - Google Patents
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Abstract
The invention discloses a construction method and an identification method of an identification model of a malt processed product, wherein the identification method of the malt processed product adopts a high performance liquid chromatography to obtain a liquid phase spectrum of an object to be detected; the liquid phase spectrum comprises at least 2 significant difference components and 1 internal standard component, the relative peak area of the significant difference components compared with the internal standard components is obtained, the relative peak area of each significant difference component obtained by detecting the object to be detected is compared with the identification model, and the judgment of the malt preparation product type is realized. The method can rapidly and accurately distinguish different malt processed products and the types of the water extracts thereof, and is very simple and convenient to operate.
Description
Technical Field
The invention relates to the field of traditional Chinese medicine identification, in particular to a method for constructing an identification model of malt processed products and an identification method.
Background
The fructus Hordei Germinatus is processed product of mature fruit of Hordeum vulgare L. Soaking wheat grains in water, maintaining proper temperature and humidity, and sun drying or low temperature drying when the buds grow to about 5 mm. Is a common clinical digestion-promoting medicine, has sweet and flat nature, enters spleen and stomach channels, and has the effects of promoting qi circulation, promoting digestion, strengthening spleen, stimulating appetite, and promoting lactation and eliminating swelling. According to the processing method, the raw malt, the roasted malt and the burnt malt are classified. Different processed products have different effects, and the raw malt has the effects of strengthening spleen and stomach, soothing liver and promoting qi circulation, and is used for spleen deficiency, anorexia and milk stasis; the stir-baked malt is indicated for indigestion and women's weaning milk, while the burnt malt is better for resolving food stagnation.
In the literature of UPLC-Q-TOF-MS/MS and network pharmacology based malt biological alkali chemical substances and pharmacodynamics research, hubei traditional Chinese medicine university 2021 (09), tao Jia, the identification of chemical components in different products of malt by using UPLC-MS/MS means is disclosed, 33 components are identified altogether, alkaloid is mainly found in the malt and the roasted malt, and the reduction of alkaloid in the scorched malt is more, and organic acid is mainly found; and establishes the content determination method of N-methyltyramine, barley malt alkali and donut-shaped bamboo reed alkali in different products of malt, and determines the content change of the three. Meanwhile, other documents in the prior publications also disclose malt HPLC fingerprints, which determine 19 common peaks and introduce the component changes in different products.
However, the above-mentioned components of the prior art are all determined by the content of the corresponding characteristic components, and the content detection is required during the determination process, thus the operation is complex; in addition, the contents of the original components in the raw materials are different, and the type of the processed product is not accurately judged only by the content of the characteristic components, so that the problem that different malt processed products cannot be effectively and rapidly distinguished still exists in the prior art.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to overcome the problem that the prior art does not disclose that different malt products can be effectively and rapidly distinguished; therefore, the method for identifying the malt processed variety by using the constructed identification model can effectively and quickly distinguish different malt processed variety types, the construction method thereof and the method for identifying the malt processed variety types by using the constructed identification model are provided.
A method of model construction for identifying malt preparations, comprising:
performing high performance liquid chromatography detection on known malt processed products to obtain chromatograms of the malt processed products;
screening out at least 10 common peaks with larger peak areas from the chromatograms of all malt preparations as characteristic peaks;
carrying out normalization processing on peak areas of the characteristic peaks, comparing aggregation distribution conditions of the characteristic peaks of various malt products by adopting a principal component analysis method, and respectively carrying out pairwise analysis on all malt product types by utilizing orthogonal partial least squares discriminant analysis to obtain at least 2 significant difference components and 1 internal standard component;
and (3) obtaining the relative peak area of the significant difference component in the chromatogram compared with the internal standard component, and dividing the ratio range of the significant difference component in each malt processed product according to the ratio of the relative peak area of the significant difference component, wherein the ratio range is the identification model of the malt processed product type.
The principal component analysis method and the orthogonal partial least squares discriminant analysis can be realized by adopting SIMCA statistical analysis software or SPSS statistical analysis software;
when the SIMCA statistical analysis software is adopted to divide the significant difference component and the internal standard component, the significant difference component is a component with VIP more than or equal to 1.5, and the internal standard component is a component with VIP less than 1.5.
The malt processed product comprises raw malt, roasted malt and burnt malt.
The number of the characteristic peaks is more than or equal to 15.
The malt preparation identification model is constructed by adopting the malt preparation identification model construction method.
An identification model of malt processed products comprises 2 significant difference components and 1 internal standard component, wherein the 2 significant difference components are 5-hydroxymethylfurfural and ferulic acid respectively, and the internal standard component is medicagin; the relative peak area ranges obtained for the significant difference component compared to the internal standard component are:
malt preparation: the relative peak area of the peak of the 5-hydroxymethylfurfural is more than or equal to 1.20;
malt production: the relative peak area of the peak of the 5-hydroxymethylfurfural is less than 1.20 and the relative peak area of the peak of the ferulic acid is more than 0.93;
malt frying: the relative peak area of the peak of the 5-hydroxymethylfurfural is less than 1.20, and the relative peak area of the peak of the ferulic acid is less than or equal to 0.93.
The significant difference component further comprises at least 8 additional components; the characteristic peak of the alfalfa is peak 8, the characteristic peak of the 5-hydroxymethylfurfural is peak 2, and the characteristic peak of the ferulic acid is peak 11; the characteristic peaks corresponding to the other 8 components are named as peak 3, peak 4, peak 6, peak 7, peak 9, peak 10, peak 13 and peak 14 in sequence according to the peak outlet time; the relative retention time of each characteristic peak is + -10% of a predetermined value, and the predetermined value comprises: 0.32 for peak 2, 0.40 for peak 3, 0.66 for peak 4, 0.75 for peak 6, 0.80 for peak 7, 1.00 for peak 8, 1.08 for peak 9, 1.09 for peak 10, 1.12 for peak 11, 1.42 for peak 13, and 1.46 for peak 14;
the relative peak area ranges obtained for the significant difference component compared to the internal standard component are:
malt production: peak 2 < 1.20, peak 3 < 0.70, peak 4 > 1.45, peak 6 < 0.74, peak 7 < 1.95, peak 9 > 0.37, peak 10 > 0.90, peak 11 > 0.93, peak 13 > 0.30, peak 14 < 0.28;
malt frying: peak 2 < 1.20,0.70 less than or equal to Peak 3 less than or equal to 1.50, peak 6 > 0.74, peak 7 > 1.95,0.21 less than or equal to Peak 9 less than or equal to 0.37, peak 10 > 0.90, peak 11 less than or equal to 0.93, peak 13 less than or equal to 0.30, peak 14 > 0.28;
malt preparation: peak 2 is more than or equal to 1.20, peak 3 is more than 1.50, peak 4 is less than 1.45, peak 6 is more than 0.74, peak 7 is more than 1.95, peak 9 is less than 0.21, peak 10 is less than or equal to 0.90, peak 13 is less than or equal to 0.30, and peak 14 is less than or equal to 0.28.
A method for identifying malt processed product comprises obtaining liquid phase diagram of the object to be detected by high performance liquid chromatography; and (3) obtaining the relative peak area of the significant difference component compared with the internal standard component, and comparing the relative peak area of each significant difference component obtained by detecting the object to be detected with the identification model constructed by the method for constructing the model for identifying the malt processed product or the identification model of one malt processed product so as to judge the type of the malt processed product.
When the number of the significant difference components is greater than or equal to 10, judging the number of the characteristic peaks of each significant difference component in the object to be detected, the relative peak areas of which fall into the numerical range of the corresponding characteristic peaks in the identification model, and if the number of the characteristic peaks falling into the numerical range is greater than or equal to 80% of the total number of the significant difference components, judging that the object to be detected belongs to the corresponding malt processed product type in the identification model.
The object to be detected is a malt processed product or an aqueous extract of the malt processed product; the water extract of the malt processed product is water extract, concentrated solution, drying liquid or formula particles.
The chromatographic conditions of the high performance liquid chromatography are as follows:
chromatographic column: chromatographic column with HSS T3 bonded silica gel as filler; the detection wavelength is 305-315 nm; acetonitrile is taken as a mobile phase A, 0.08-0.12% formic acid aqueous solution is taken as a mobile phase B, and elution is carried out according to the following gradient elution program, wherein:
the column temperature of the chromatographic column in the high performance liquid chromatography is 28-32 ℃; the specification of the chromatographic column is 2.1X105 mm, 1.8 μm; the flow rate is 0.285-0.315 ml/min, and the theoretical plate number is not less than 5000 calculated according to alfalfa element peaks.
The preparation process of the sample solution used in the high performance liquid chromatography comprises the following steps: and (3) taking an object to be detected, adding a solvent, processing, and filtering to obtain a filtrate, wherein the filtrate is the solution of the object to be detected.
In the preparation process of the sample solution, the treatment is ultrasonic treatment; the solvent is 40-60% methanol water solution.
The ultrasonic treatment time is 20-60 minutes.
The technical scheme of the invention has the following advantages:
1. according to the method for constructing the model for identifying the malt processed products and the formula particles thereof, the significant difference components of different processed products can be effectively determined, the identification model for judging the types of the malt processed products can be obtained by combining the design of the ratio range of the relative peak areas of the significant difference components, and the types of different processed products can be effectively and rapidly distinguished by comparing the ratio range of the relative peak areas of the characteristic peaks of the significant difference components in the to-be-detected objects compared with the S peak with the identification model, so that the method is simple and convenient to operate.
2. In the method for identifying the malt processed products, the salient difference components in the model for identifying the types of the malt processed products at least comprise 5-hydroxymethyl furfural and ferulic acid, the internal standard component is alfalfa element, and the types of different processed products can be effectively and rapidly distinguished by only detecting the ratio result of the characteristic peak of the salient difference components of the to-be-detected object to the relative peak area of the characteristic peak of the alfalfa element and comparing the ratio result with the range of the peak areas of the characteristic peaks corresponding to the salient difference components in the identification model.
3. In the detection process, the peak area of the individual characteristic peak is smaller or other reasons such as a process and the like possibly cause that the relative peak area of the characteristic peak where the significant difference component is located in the processed product has a discrete value, and the result is easy to be inaccurate, so that the identification method in the invention provides the range value of the relative peak area of the characteristic peak where the identification model at least comprises 10 significant difference components, and the type of the malt processed product to which the object to be detected belongs can be determined as long as the number of the characteristic peaks more than 80% meet the ratio, and the judgment result is more accurate and reliable.
4. The identification method can also be used for judging the end point of the processing technology, so that the processing quality is more stable; meanwhile, the invention does not need quantitative characterization and calculation of the object to be detected; the data does not need to be imported into software for secondary analysis, so that time and labor are saved.
5. The invention further optimizes the high performance liquid chromatography condition in the identification method, can obtain at least 10 characteristic peaks with obviously changed component content in the processing process, and effectively provides an effective premise for accurately identifying the variety of malt products.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a liquid phase control plot of three malt preparations in example 1 of the present invention.
Detailed Description
The specific experimental procedures or conditions are not noted in the examples and may be followed by the operations or conditions of conventional experimental procedures described in the literature in this field. The reagents or apparatus used were conventional reagent products commercially available without the manufacturer's knowledge.
Instrument: waters ultra-high Performance liquid chromatograph (PDA ultraviolet detector), electronic balance (ML 204T type, metrele Torison instruments Co., ltd.), electronic balance (JJ 500 type, double Jie test instruments Co., ltd.), ultrasonic cleaner (KQ-100 DE type, kunshan ultrasonic instruments Co., ltd.), water bath constant temperature oscillator (THZ-82 type, jintan Jinda instruments Co., ltd.), chromatographic column: waters ACQUITY
HSS T3(2.1*150mm，1.8μm)。
Reagent: acetonitrile (Merck) is chromatographically pure; phosphoric acid (Thermo) is chromatographically pure; the water is distilled water (Chen's); the other reagents were all analytically pure.
Example 1
The model construction method for identifying malt products comprises the following specific processes:
1. taking 14 batches of samples (raw malt particles, roasted malt particles and burnt malt particles) of formula particles of different products, grinding, preparing a test solution according to the following method, detecting, and obtaining a liquid phase map.
Wherein, the batch numbers of the raw malt particles are respectively: 20003572, 20003582, 20003592, 20003602;
the lot numbers of the roasted malt particles are respectively as follows: 19019753, 19017301, 20042891, 20006521, 20006511;
the lot numbers of the scorched malt particles are respectively: 20022481, 20022491, 20005381, 20005391, 20005401.
(1) Preparation of a control solution: weighing reference substances of alfalfa extract, 5-hydroxymethylfurfural and ferulic acid, adding 50% methanol for dissolving, and preparing into solutions containing 5 μg, 10 μg and 1 μg respectively per 1 mL;
(2) Preparation of test solution: grinding the materials, taking about 1.0g, precisely weighing, placing in a conical flask, precisely adding 25ml of 50% methanol, sealing, weighing, performing ultrasonic treatment (power 500W, frequency 40 kHz) for 20 minutes, cooling, weighing again, supplementing the reduced weight with 50% methanol, shaking uniformly, filtering, taking 15ml of the continuous filtrate, evaporating to dryness, dissolving in 5ml volumetric flask with 50% methanol, fixing volume, shaking uniformly, and filtering to obtain the product.
(3) Chromatographic conditions
Chromatographic column: HSS T3 bonded silica gel is used as a filler, the column length is 150mm, the inner diameter is 2.1mm, and the granularity is 1.8 mu m;
column temperature: 30 ℃;
mobile phase: acetonitrile is taken as a mobile phase A, and 0.1% formic acid water solution is taken as a mobile phase B;
mobile phase flow rate: 0.3mL/min;
sample injection amount: 3 μL;
detection wavelength: 310nm;
the number of theoretical plates is not less than 5000 according to alfalfa element peaks;
the mobile phase was subjected to gradient elution as shown in table 1 below, specifically:
TABLE 1
The elution procedure of Table 1 was followed to obtain a liquid phase pattern of 14 samples.
2. Data processing of liquid phase pattern
(1) Obtaining a common peak:
the liquid phase spectra of the three processed product particles measured by using the "traditional Chinese medicine chromatographic fingerprint similarity evaluation system" (2012.1 version) are all analyzed and compared by taking the first batch of S1 liquid phase spectra as reference spectra, and 15 peaks with larger peak areas and better separation effect in the common peaks are finally selected as characteristic peaks, and the 15 characteristic peaks are sequentially named as peak 1-peak 15 in the embodiment, and the chromatograms of different processed products are shown in fig. 1.
(2) And obtaining the significant difference component and the internal standard component in the characteristic peak.
In the present embodiment, the difference between the significant difference component and the internal standard component of the 14 batches of samples is obtained by using SIMCA statistical analysis software as an example.
Specifically, 15 characteristic peak areas of 14 batches of samples (raw malt particles, roasted malt particles and scorched malt particles) are subjected to normalization treatment, SIMCA-P14.1 software is adopted for pattern recognition, the aggregation distribution conditions of raw malt, roasted malt and scorched malt are compared by using a principal component analysis method of a PCA module, the analysis is respectively carried out in pairs by using an orthogonal partial least squares discriminant analysis (OPLS-DA), difference Variables (VIP) are screened by the OPLS-DA, the significant difference components corresponding to the characteristic peaks are screened by taking VIP >1.5 as a standard, and the screened significant difference components can be selected as quality markers for carrying out the product identification.
According to analysis results of processed products, the ratio of the raw malt to the scorched malt can show that the continuous change of the content of different components in the processing process is realized, some peaks are sensitive to heat, and the change of the peak is obvious in the stir-frying stage, so that the method can be used for distinguishing the raw product from the processed product, and some peaks are less sensitive, and the method can be used for distinguishing the raw malt, the stir-fried malt and the scorched malt particles after being heated for a long time. From the screening results, it was found that the raw malt and the roasted malt particles were discriminated by peaks 3, 6, 7, 9, 11, 13 and 14, the raw malt and the roasted malt particles were discriminated by peaks 2, 3, 4, 6, 7, 9, 10 and 13, and the roasted malt particles were discriminated by peaks 2, 3, 9, 10 and 14. Peak 3 and Peak 9 can distinguish raw products from processed products (roasted malt and roasted malt) at the same time.
Meanwhile, through screening a difference Variable (VIP) by OPLS-DA, selecting one component with the VIP less than 1.5 as an Internal Standard (IS), wherein the content of the internal standard IS not greatly changed in the processing process, the separation effect IS good, and the peak area IS moderate. The Internal Standard (IS) selected in this example was the medicagin of peak 8.
(3) The range of relative peak areas of the significant difference components in each malt preparation compared to the internal standard components was determined.
Comparing the significant difference component selected in the step (2) with the peak area of the internal standard to obtain a relative peak area, and counting the ratio range of the relative peak areas of different significant difference components of different processed products, wherein the ratio range of the peak areas of the significant difference components of the 14 batches of different processed products is shown in the following table 2:
TABLE 2
By the ratio range of the peak areas of the above significant difference components, the critical values of different product discrimination can be determined, and the determined critical values in this example are shown in the following table 3:
TABLE 3 Table 3
Note that: -the representation range is not applicable
In the invention, the relative peak area ranges of at least two significant difference components capable of realizing the distinction of three malt preparation types can be directly screened out from the table 3, namely, the method can be used as a malt preparation type distinguishing model, for example, 5-hydroxymethylfurfural of peak 2 and ferulic acid of peak 11 are screened out, and the distinction of the malt preparation types can be realized through the relative peak area ranges of the two significant difference components. The identification model consisting of these two significantly different components is:
malt preparation: the relative peak area of the peak of the 5-hydroxymethylfurfural is more than or equal to 1.2;
malt production: the relative peak area of the peak of the 5-hydroxymethylfurfural is less than 1.2 and the relative peak area of the peak of the ferulic acid is more than 0.93;
malt frying: the relative peak area of the peak of the 5-hydroxymethylfurfural is less than 1.2, and the relative peak area of the peak of the ferulic acid is less than or equal to 0.93.
Further, since the discrete values of the characteristic peaks in the processed product are caused by the smaller areas of the individual characteristic peaks or other reasons such as the process, in order to obtain higher identification accuracy, the ratio ranges in table 3 are all included in the identification model of the malt processed product type, and in this embodiment, the ratio coincidence range of 80% (i.e. 8 or more) of the characteristic peaks is specified to be used for determining the type of the sample, so that the determination result is more accurate.
Example 2
A malt preparation identification method adopts the identification model obtained in the embodiment 1 to carry out judgment, and the specific process is as follows:
3 batches of the formula particles of the known kinds of malt preparations were obtained, and the batch numbers of the formula particles of the respective malt preparations are shown in Table 4 below.
TABLE 4 Table 4
The liquid chromatogram was obtained by the same high performance liquid chromatography detection method as in example 1, and the ratio of the peak areas of 10 characteristic peaks in total of 2, 3, 4, 6, 7, 9, 10, 11, 13, 14 to the internal standard was calculated, and the results are shown in table 5 below.
TABLE 5 relative peak areas of the various significantly different components of the three malt preparation formulation granules
The results obtained in Table 5 above show that the relative peak area ranges of the respective significantly different components match the discrimination models shown in Table 3. Therefore, the identification model can be effectively used for identifying malts, roasted malts and scorched malts, and the accuracy of the identification result is high.
Example 3
The difference between this example and example 1 is that the preparation conditions of the sample solution are different, specifically:
1. solvent volume investigation of test solution
Respectively weighing raw malt formula particles (batch number: 20003572), weighing 1g in parallel, precisely weighing, placing into a conical flask with a plug, precisely adding 15ml, 25ml and 50ml of 50% methanol, weighing, performing ultrasonic extraction (power 500W and frequency 40 kHz), taking out, cooling, weighing again, supplementing the lost weight with 50% methanol, shaking uniformly, filtering, precisely measuring a certain volume (60% of the added volume) of the continuous filtrate, evaporating, dissolving in a 5ml volumetric flask with 50% methanol, fixing volume, shaking uniformly, and filtering to obtain the product. The relative retention times and relative peak areas of characteristic peaks 1 to 15 were calculated with peak number 8 as reference peak S, and RSD was calculated.
The relative retention times and relative peak areas of the characteristic peaks of the various volume extracted samples are shown in tables 6 and 7.
TABLE 6 extraction solvent volume investigation relative Retention timetable
TABLE 7 extraction solvent volume investigation relative peak area table
The results show that when the volumes of the extraction solvents are 15ml, 25ml and 50ml, the relative peak areas of the characteristic peaks are greatly influenced, but the RSD is less than 10%, so that the discrimination requirements are met. The extraction solvent volume was determined to be 25ml in combination with the relative peak area considerations.
2. Ultrasonic time investigation of test solutions
Respectively weighing raw malt formula particles (batch number: 20003582), weighing 1g in parallel, precisely weighing, placing into a conical flask with a plug, precisely adding 25ml of 50% methanol, weighing, ultrasonically extracting (power 500W, frequency 40 kHz) for 20 minutes, 40 minutes and 60 minutes, taking out, cooling, weighing again, supplementing the lost weight with 50% methanol, shaking uniformly, filtering, precisely measuring 15ml of the continuous filtrate, evaporating to dryness, dissolving in a 5ml volumetric flask with 50% methanol, fixing volume, shaking uniformly, and filtering to obtain the product. The relative retention times and relative peak areas of characteristic peaks 1 to 15 were calculated with peak number 8 as reference peak S, and RSD was calculated. The relative retention time and relative peak area results are shown in tables 8 and 9.
Table 8 different ultrasound time surveys of the relative retention time table
Table 9 table of relative peak areas for different ultrasonic time surveys
The results show that the RSD of the relative peak areas of the characteristic peaks is less than 10% and the relative retention time is less than 0.5% when the ultrasonic time is 20 minutes, 40 minutes and 60 minutes, so the extraction time is 20-60 minutes.
Example 4
This example was used to methodologically verify the conditions of high performance liquid chromatography in example 1, and included:
1. repeatability verification
Taking 6 parts of raw malt particles (batch number: 20003592), determining according to the method of example 1, obtaining a characteristic map, and calculating the relative retention time and relative peak area of characteristic peaks of numbers 1-15 by taking peak 8 as reference peak S; and calculates RSD. The results are shown in tables 10 and 11.
Table 10 feature map repeatability investigation relative retention time table
TABLE 11 relative peak area table for feature map repeatability investigation
According to the repeatability inspection result, the relative retention time RSD of each characteristic peak is in the range of less than 0.2%, and the relative peak area RSD of other characteristic peaks is in the range of 0.00% -6.13%, which shows that the characteristic peak repeatability of the characteristic map is better.
2. Precision verification
Taking raw malt particles (batch number: 20003592), preparing 6 samples at different times by different analysts to perform intermediate precision test, determining according to a text method to obtain a characteristic map, and calculating the relative retention time and the relative peak area of each characteristic peak by taking a No. 8 peak as a reference peak S; the RSD values were calculated as shown in table 12 with the results of the repeatability study.
Table 12 intermediate precision investigation relative retained peak area table
From the above results, it can be seen that: the relative peak area RSD of each characteristic peak of the prepared sample by different personnel at different time ranges from 0.00% to 6.03%, which shows that the analysis method has good intermediate precision.
3. Stability verification
Taking raw malt particles (batch number: 20003592), preparing a sample solution according to a text method, measuring at 0, 3, 6, 9, 12 and 24 hours according to the text method respectively, obtaining a characteristic map, and calculating the relative retention time and the relative peak area of each characteristic peak by taking a No. 8 peak as a reference peak S; and calculates RSD. The results are shown in tables 13 and 14.
TABLE 13 stability versus retention time table
Table 14 stability versus peak area table
As a result of the above-mentioned stability test, 15 characteristic peaks in the sample solution were each less than 3% in relative retention time and relative peak area, and the sample was considered to be stable at room temperature for 24 hours.
Example 5
A malt preparation identification method adopts the identification model obtained in the embodiment 1 to carry out judgment, and the specific process is as follows:
3 batches of malt preparations and their formulation particles of known types were obtained, and the batch numbers of each malt preparation and its formulation particle were the same as those shown in Table 4 in example 2.
Chromatographic conditions are chromatographic column: HSS T3 bonded silica gel is used as a filler, the column length is 150mm, the inner diameter is 2.1mm, and the granularity is 1.8 mu m; column temperature: 28 ℃; mobile phase: acetonitrile is taken as a mobile phase A, and 0.12% formic acid water solution is taken as a mobile phase B; mobile phase flow rate: 0.315mL/min; sample injection amount: 3 μL; detection wavelength: 305nm;
a liquid chromatogram was obtained by the same mobile phase gradient test as in example 1, and the ratios of the peak areas of the peaks 2, 3, 4, 6, 7, 9, 10, 11, 13, 14, which were 10 characteristic peaks, to the internal standard were calculated, and the results are shown in table 15 below.
Table 15: relative peak area of each significant difference component of the three malt processed product formula particles
Note that: -the representation range is not applicable, no calculation of the relative peak area is performed
The results obtained by the above table can be effectively shown: the identification method has higher accuracy and can be used for identifying raw malt, roasted malt and scorched malt formula particles.
Example 6
A malt preparation identification method adopts the identification model obtained in the embodiment 1 to carry out judgment, and the specific process is as follows:
3 batches of malt preparations and their formulation particles of known types were obtained, and the batch numbers of each malt preparation and its formulation particle were the same as those shown in Table 4 in example 2.
Chromatographic conditions are chromatographic column: HSS T3 bonded silica gel is used as a filler, the column length is 150mm, the inner diameter is 2.1mm, and the granularity is 1.8 mu m; column temperature: 32 ℃; mobile phase: acetonitrile is taken as a mobile phase A, and 0.08% formic acid water solution is taken as a mobile phase B; mobile phase flow rate: 0.285mL/min; sample injection amount: 3 μL; detection wavelength: 315nm;
a liquid chromatogram was obtained by the same mobile phase gradient test as in example 1, and the ratios of the peak areas of the peaks 2, 3, 4, 6, 7, 9, 10, 11, 13, 14, which were 10 characteristic peaks, to the internal standard were calculated, and the results are shown in table 16 below.
TABLE 16 relative peak areas of the various significantly different components of the three malt processed product formulas
The results obtained by the above table can be effectively shown: the identification method has higher accuracy and can be used for identifying raw malt, roasted malt and scorched malt formula particles.
It is apparent that the above examples are given by way 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 (13)
1. A method of constructing a model for identifying malt-based products, comprising:
detecting with known malt processed products by high performance liquid chromatography to obtain chromatograms of the malt processed products;
screening out at least 10 common peaks with larger peak areas from the chromatograms of all malt preparations as characteristic peaks;
carrying out normalization processing on peak areas of the characteristic peaks, comparing aggregation distribution conditions of the characteristic peaks of various malt products by adopting a principal component analysis method, and respectively carrying out pairwise analysis on all malt product types by utilizing orthogonal partial least squares discriminant analysis to obtain at least 2 significant difference components and one internal standard component; the significant difference component comprises 5-hydroxymethyl furfural and ferulic acid, and the internal standard component is medicagin;
obtaining the relative peak area of the significant difference component in the chromatogram compared with the internal standard component, and dividing the ratio range of the significant difference component in various malt products according to the ratio of the relative peak area of the significant difference component, wherein the ratio range is the identification model of the malt products;
the chromatographic conditions of the high performance liquid chromatography are as follows:
chromatographic column: chromatographic column with HSS T3 bonded silica gel as filler; the specification of the chromatographic column is 2.1X105 mm, 1.8 μm; acetonitrile is used as a mobile phase A, 0.08-0.12% formic acid aqueous solution is used as a mobile phase B, and elution is carried out according to the following gradient elution procedure, wherein:
2. the model construction method according to claim 1, wherein the principal component analysis method and the orthorhombic partial least squares discriminant analysis can be implemented using SIMCA or SPSS statistical analysis software;
when the SIMCA statistical analysis software is adopted to divide the significant difference component and the internal standard component, the significant difference component is a component with VIP more than or equal to 1.5, and the internal standard component is a component with VIP less than 1.5.
3. The model construction method according to claim 1 or 2, wherein the types of malt preparations include raw malt, roasted malt, and burnt malt;
the number of the characteristic peaks is more than or equal to 15.
4. The model construction method according to claim 1 or 2, wherein the constructed identification model comprises 2 significant difference components and 1 internal standard component, wherein the 2 significant difference components are 5-hydroxymethylfurfural and ferulic acid respectively, and the internal standard component is medicagin; the relative peak area ranges obtained for the significant difference component compared to the internal standard component are:
malt preparation: the relative peak area of the peak of the 5-hydroxymethylfurfural is more than or equal to 1.20;
malt production: the relative peak area of the peak of the 5-hydroxymethylfurfural is less than 1.20 and the relative peak area of the peak of the ferulic acid is more than 0.93;
malt frying: the relative peak area of the peak of the 5-hydroxymethylfurfural is less than 1.20, and the relative peak area of the peak of the ferulic acid is less than or equal to 0.93.
5. The model construction method according to claim 4, wherein the significant difference component further includes at least 8 other components; the characteristic peak of the alfalfa is peak 8, the characteristic peak of the 5-hydroxymethylfurfural is peak 2, and the characteristic peak of the ferulic acid is peak 11; the characteristic peaks corresponding to the other 8 components are named as peak 3, peak 4, peak 6, peak 7, peak 9, peak 10, peak 13 and peak 14 in sequence according to the peak outlet time; the relative retention time of each characteristic peak is + -10% of a predetermined value, and the predetermined value comprises: 0.32 for peak 2, 0.40 for peak 3, 0.66 for peak 4, 0.75 for peak 6, 0.80 for peak 7, 1.00 for peak 8, 1.08 for peak 9, 1.09 for peak 10, 1.12 for peak 11, 1.42 for peak 13, and 1.46 for peak 14;
the relative peak area ranges obtained for the significant difference component compared to the internal standard component are:
malt production: peak 2 < 1.20, peak 3 < 0.70, peak 4 > 1.45, peak 6 < 0.74, peak 7 < 1.95, peak 9 > 0.37, peak 10 > 0.90, peak 11 > 0.93, peak 13 > 0.30, peak 14 < 0.28;
malt frying: peak 2 < 1.20,0.70 less than or equal to Peak 3 less than or equal to 1.50, peak 6 > 0.74, peak 7 > 1.95,0.21 less than or equal to Peak 9 less than or equal to 0.37, peak 10 > 0.90, peak 11 less than or equal to 0.93, peak 13 less than or equal to 0.30, peak 14 > 0.28;
malt preparation: peak 2 is more than or equal to 1.20, peak 3 is more than 1.50, peak 4 is less than 1.45, peak 6 is more than 0.74, peak 7 is more than 1.95, peak 9 is less than 0.21, peak 10 is less than or equal to 0.90, peak 13 is less than or equal to 0.30, and peak 14 is less than or equal to 0.28.
6. A method for identifying malt products is characterized in that a high performance liquid chromatography is adopted to obtain a liquid phase map of an object to be detected; obtaining the relative peak area of the significant difference component compared with the internal standard component, and comparing the relative peak area of each significant difference component obtained by detecting the object to be detected with the identification model constructed by the model construction method for identifying the malt processed product according to any one of claims 1-5, so as to realize the judgment of the type of the malt processed product.
7. The method according to claim 6, wherein when the number of the significant difference components is greater than or equal to 10, determining that the relative peak area of the characteristic peak where each significant difference component is located in the object to be tested falls into the number range of the corresponding characteristic peak in the identification model, and if the number of the characteristic peaks falling into the number range is greater than or equal to 80% of the total number of the significant difference components, determining that the object to be tested belongs to the corresponding malt preparation class in the identification model.
8. The method according to claim 6 or 7, wherein the test substance is malt preparation or an aqueous extract of malt preparation; the water extract of the malt processed product is water extract, concentrated solution and drying solution.
9. The method according to claim 6 or 7, wherein the chromatographic conditions of the high performance liquid chromatography are:
the detection wavelength is 305-315 nm.
10. The identification method according to claim 9, wherein the column temperature of the chromatographic column in the high performance liquid chromatography is 28-32 ℃; the flow rate is 0.285-0.315 ml/min, and the theoretical plate number is not lower than 5000 according to alfalfa pixel peaks.
11. The method according to claim 9, wherein the preparation process of the sample solution used in the high performance liquid chromatography is: and (3) taking an object to be detected, adding a solvent, processing, and filtering to obtain a filtrate, wherein the filtrate is the solution of the object to be detected.
12. The method of claim 11, wherein the treatment is an ultrasonic treatment during the preparation of the test solution; the solvent is 40-60% methanol water solution.
13. The method of claim 12, wherein the sonication time is 20-60 minutes.
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