A method for identifying wolfberry puree processed in different ways

Abstract

The present invention discloses a method for identifying wolfberry puree with different processing methods, and belongs to the technical field of food science analytical chemistry. The method for identifying wolfberry puree with different processing methods comprises the following steps: using gas chromatography-ion mobility spectrometry to detect the volatile components of standard products of wolfberry puree with different processing methods, and obtaining GC-IMS sample data; using GC-IMS software to classify the types, and obtaining different types of volatile components; using partial least squares-discriminant analysis method to analyze different types of variable projection importance values, and screening out volatile component characteristic markers according to the variable projection importance values; comparing the volatile components of the wolfberry puree to be tested with the volatile component characteristic markers to identify the processing method of the wolfberry puree to be tested. The present invention is based on GC-IMS technology and utilizes the significance of volatile flavor substances in different wolfberry purees to evaluate the processing method of wolfberry puree.

Description

Technical Field

[0001] The invention relates to the technical field of food science analytical chemistry, and more specifically to a method for identifying wolfberry purees processed in different ways. Background Art

[0002] Fresh wolfberry fruit is not suitable for long-term storage and has a relatively short shelf life, so its main processing method is drying. In recent years, wolfberry puree has gradually emerged and become a leading product in the consumer market, winning wide favor from consumers. There are many types of wolfberry puree products on the market, and the processing methods are also different, mainly non-concentrated and reduced (Not From Concentrate, NFC) wolfberry puree, concentrated and reduced (From Concentrate, FC) wolfberry puree and wolfberry dried fruit rehydrated puree. In comparison, NFC wolfberry puree can maintain the nutritional value and taste of fresh wolfberry fruit to the greatest extent, and also effectively prevents the nutritional loss and contamination caused by the drying or smoking of raw materials. The volatile substances in wolfberry puree play a decisive role in its flavor quality and taste.

[0003] At present, the research on the quality of wolfberry puree is mostly based on the analysis of physical and chemical indicators, which is not comprehensive and cannot effectively distinguish wolfberry purees with different processing methods. Fundamentally speaking, volatile components not only play a decisive role in the flavor quality of wolfberry puree, but also affect its taste. Therefore, it is of great significance to explore the volatile components of wolfberry puree. The processing method will affect the volatile components. Different processing methods will cause changes in volatile components. These changes will affect the flavor and quality of wolfberry puree. Therefore, by detecting volatile components, the flavor and taste of the product during the processing process can be monitored. In recent years, the instruments for detecting volatile components in food are mostly gas chromatography-mass spectrometry. This instrument has high sensitivity, but the detection time is long, the operation requirements are high, and the analysis and identification are complex, so it is not suitable for rapid detection. Summary of the invention

[0004] In view of the above problems, the present invention provides a method for identifying wolfberry puree with different processing methods. The present invention quickly identifies different wolfberry puree samples based on GC-IMS technology, and uses the significance of volatile flavor substances in different wolfberry purees to quickly identify, thereby evaluating the processing method of wolfberry puree.

[0005] The present invention provides a method for identifying wolfberry purees processed in different ways, comprising the following steps:

[0006] The volatile components of the standard samples of wolfberry puree processed in different ways were detected by gas chromatography-ion mobility spectrometry to obtain GC-IMS sample data.

[0007] GC-IMS software was used to classify the GC-IMS sample data and obtain different types of volatile components;

[0008] The partial least squares-discriminant analysis method was used to analyze the variable projection importance values ​​of different types of volatile components, and the characteristic markers of volatile components were screened out according to the variable projection importance values.

[0009] The wolfberry puree to be tested is analyzed by gas chromatography-ion mobility spectrometry to obtain the volatile components of the wolfberry puree to be tested, and the volatile components of the wolfberry puree to be tested are compared with the characteristic markers of the volatile components to identify the processing method of the wolfberry puree to be tested.

[0010] In a preferred embodiment of the present invention, the method of classifying is as follows: according to the retention index of the standard substance in the GC-IMS software and the retention time determined experimentally, the GC-IMS sample data is classified using the Reporter plug-in, the Gallery Plot plug-in, and the GC×IMS Library Search software.

[0011] In a preferred embodiment of the present invention, the different types of volatile components include aldehydes, alcohols, ketones, esters, heterocycles, hydrocarbons, acids and ethers.

[0012] In a preferred embodiment of the present invention, the projection importance value of the variable corresponding to the characteristic marker of the volatile component is screened out to be greater than 1.

[0013] In a preferred embodiment of the present invention, wolfberry puree processed in different ways includes non-concentrated and reconstituted wolfberry puree, concentrated and reconstituted wolfberry puree and wolfberry dried fruit rehydrated puree.

[0014] In a preferred embodiment of the present invention, the characteristic markers of volatile components of the standard sample of non-concentrated reduced wolfberry puree are (E,E)-2,4-heptadienal, 2-ethyl-6-methylpyrazine, 3-hexanone, 2-hexenal, ethyl acetate, ethyl isobutyrate, 2-n-butylfuran and (E)-2-heptenal. When the above compounds are simultaneously analyzed from the wolfberry puree to be tested, the processing method is the non-concentrated reduction method.

[0015] In a preferred embodiment of the present invention, the characteristic markers of volatile components of the standard concentrated and reduced wolfberry puree are 2-n-pentylfuran, heliotropin propylene glycol acetal, 2-methylbutanal, isobutyraldehyde, isovaleraldehyde, 2-methyl-3-furanthiol, heptaldehyde and phellandrene. When the above compounds are simultaneously analyzed from the wolfberry puree to be tested, the processing method is the concentration reduction method.

[0016] In a preferred embodiment of the present invention, the characteristic markers of volatile components of the standard sample of wolfberry dried fruit rehydrated puree are n-butyraldehyde, 6-benzylaminopurine and furfural monomers. When the above compounds are simultaneously analyzed out of the wolfberry puree to be tested, the processing method is the wolfberry dried fruit rehydration method.

[0017] In a preferred embodiment of the present invention, the detection conditions of gas chromatography are: MXT-5 gas chromatography column, column temperature is 40°C; carrier gas is nitrogen with a purity of 99.99%, and the initial flow rate of the carrier gas flow system is 2mL / min, maintained for 2min, 15mL / min maintained for 10min, the flow rate is increased to 100mL / min and maintained for 20min, and the flow rate is increased to 150mL / min for 30min.

[0018] In a preferred embodiment of the present invention, the ion mobility spectrometry conditions are: the temperature is 45° C., the E1 drift gas flow rate is 150 mL / min, and the drift gas is nitrogen with a purity of 99.99%.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] The present invention adopts GC-IMS technology to analyze wolfberry puree to obtain the fingerprint spectrum of the wolfberry puree sample, and then uses the partial least squares method-discriminant analysis method to screen out characteristic markers through the variable importance in projection (VIP) value, and judges the processing method of the unknown wolfberry puree through the characteristic markers.

[0021] The present invention adopts GC-IMS analysis to identify a total of 4 characteristic volatile compounds, including 15 aldehydes, 8 alcohols, 6 ketones, 6 esters, 6 heterocyclics, 2 hydrocarbons, and 1 acid and 1 ether, and the relative content in different wolfberry purees is different. The variable projection importance values ​​of different types of volatile components are analyzed by partial least squares-discriminant analysis method. 19 characteristic markers are screened out using variable projection importance values ​​greater than 1 to identify different types of wolfberry purees, providing a method for rapid identification of wolfberry purees. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 The three-dimensional spectra of volatile substances in different wolfberry purees;

[0023] Figure 2 The two-dimensional spectra of volatile substances in different wolfberry purees;

[0024] Figure 3 The flavor fingerprints of different wolfberry purees;

[0025] Figure 4This is the principal component analysis diagram of the volatile components of different wolfberry purees;

[0026] Figure 5 This is the PLS-DA score diagram of the volatile components of different wolfberry purees;

[0027] Figure 6 This is the PLS-DA permutation test diagram of the volatile components of different wolfberry purees;

[0028] Figure 7 Characteristic volatile compounds with VIP>1 in different wolfberry purees. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in 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. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] As described in the background technology, the existing technology often uses gas chromatography-mass spectrometry to detect volatile components in food, but this instrument takes a long time to detect, has high operating requirements, and is complex to analyze and identify, making it unsuitable for rapid detection. Therefore, it is necessary to find an identification method suitable for rapid detection.

[0031] Gas Chromatography-Ion Mobility Spectroscopy (GC-IMS) has the advantages of small sample volume, relatively simple system setup, high sensitivity and high stability. It utilizes the chromatographic separation characteristics to pre-separate the volatile components of the sample to be tested into a single component, and then performs secondary separation through ion migration to obtain a three-dimensional spectrum of drift time, retention time and signal intensity. It is an emerging volatile substance analysis and detection technology in recent years and has been widely used to identify different varieties, different origins and the authenticity of food.

[0032] Based on this, the present invention provides a method for identifying wolfberry purees processed in different ways, comprising the following steps:

[0033] The volatile components of the standard samples of wolfberry puree processed in different ways were detected by gas chromatography-ion mobility spectrometry to obtain GC-IMS sample data.

[0034] GC-IMS software was used to classify the GC-IMS sample data and obtain different types of volatile components;

[0035] The partial least squares-discriminant analysis method was used to analyze the variable projection importance values ​​of different types of volatile components, and the characteristic markers of volatile components were screened out according to the variable projection importance values.

[0036] The volatile components of the wolfberry puree to be tested are analyzed by gas chromatography-ion mobility spectrometry to obtain the volatile components of the wolfberry puree to be tested, and the volatile components of the wolfberry puree to be tested are compared with the characteristic markers of the volatile components to identify the processing method of the wolfberry puree to be tested. It should be noted that GC-IMS software refers to the analysis software supporting the gas chromatography-ion mobility spectrometry instrument.

[0037] The present invention uses a simple and rapid gas chromatography-ion mobility spectrometry instrument to analyze the volatile components of wolfberry purees processed in different ways, and can intuitively reflect the differential compounds of wolfberry purees processed in different ways through fingerprints. According to the peak areas of various substances in the fingerprints of different wolfberry puree samples, chemometric analysis is performed to obtain characteristic markers of volatile components of different wolfberry purees, thereby realizing rapid identification of wolfberry purees processed in unknown ways. The method is simple to operate, does not require a complex pre-treatment process for the sample, and has a short detection time.

[0038] For wolfberry puree whose processing method is unclear, the inventors used GC-IMS technology to analyze wolfberry puree to obtain the fingerprint of wolfberry puree sample, and then used partial least squares method-discriminant analysis method to analyze the VIP values ​​of different types of volatile components, screened out characteristic markers by VIP value greater than 1, and judged the processing method of wolfberry puree by characteristic markers. During the detection process, due to the high sugar content and high viscosity of wolfberry puree, the aroma components evaporate slowly, making it difficult to separate the volatile components, which is not conducive to the detection of volatile components. To address this problem, the inventors found that the gas chromatography time was increased during the GC-IMS detection process, adjusted from 0-20min to 0-30min, so that the volatile components were better separated.

[0039] The following is further described in conjunction with specific embodiments.

[0040] Example 1

[0041] This embodiment provides a method for rapid identification of different wolfberry puree samples based on GC-IMS technology, which uses the significance of volatile flavor substances in different wolfberry purees to perform rapid identification, thereby evaluating the flavor quality of wolfberry purees. The method includes the following steps.

[0042] (1) The volatile components of the standard samples of wolfberry purees processed by different methods were detected by gas chromatography-ion mobility spectrometry, and the GC-IMS sample data were obtained as follows:

[0043] Sample pretreatment: 3 mL of wolfberry puree with different processing methods was placed in a 20 mL headspace bottle and oscillated at 60°C and 500 r / min for 10 min. Three parallels were prepared for each sample. The samples were divided into three categories: NFC wolfberry puree, FC wolfberry puree, and wolfberry dried fruit rehydrated puree.

[0044] It should be noted that NFC1, NFC2 and DHX belong to NFC wolfberry puree. The difference is that NFC1 and NFC2 are NFC wolfberry puree, and their wolfberry varieties are Keqi 608 and Ningqi No. 1 respectively, and DHX was purchased from a food company in Ningxia.

[0045] FC1 and FC2 belong to FC wolfberry puree. The difference is that their wolfberry varieties are Keqi 608 and Ningqi No. 1 respectively. The NFC wolfberry puree of the corresponding varieties is concentrated in a water bath vacuum at 60°C until the concentration reaches 65±1°Brix to obtain a concentrated solution, which is then compounded with water to the original sugar content of the NFC wolfberry puree and sterilized for use.

[0046] GG1, GG2 and GG3 are wolfberry dried fruit rehydrated puree, which are three identical samples divided into three parts for experiments. They are obtained by mixing two kinds of wolfberry dried fruits, Ningqi No. 1 and Keqi 608, in a mass ratio of 1:1 to obtain mixed wolfberries, and then adding water in a ratio of 1g:6ml to the mixed wolfberries to soak for 1h, then squeezing the juice, filtering to remove the pomace, and sterilizing.

[0047] GC conditions: MXT-5 gas chromatography column (specifications: 15m×0.53mm×1μm), column temperature: 40°C; carrier gas: 99.99% pure nitrogen, carrier gas flow system: initial flow rate: 2mL / min, maintained for 2min, 15mL / min for 10min, flow rate increased to 100mL / min for 20min, flow rate increased to 150mL / min for 30min.

[0048] IMS conditions: IMS temperature was 45°C, E1 drift gas flow rate was 150 mL / min, and the drift gas was nitrogen with a purity of 99.99%.

[0049] After testing the volatile components of standard samples of wolfberry puree with different processing methods, GC-IMS sample data were obtained.

[0050] (2) GC-IMS software is used to classify the GC-IMS sample data to obtain different types of volatile components, as follows:

[0051] The NIST database and IMS database built into the GC-IMS software were used to classify the volatile compounds detected in different wolfberry puree samples. Specifically, the volatile components were identified according to the retention index of the standard substances in the GC-IMS library and the retention time measured experimentally. The GC-IMS sample data were classified using instrument analysis software such as Reporter, Gallery Plot, and GC×IMSLibrarySearch to obtain different types of volatile components.

[0052] A total of 48 volatile components were detected, and 45 typical volatile flavor compounds were identified, including 15 aldehydes, 8 alcohols, 6 ketones, 6 esters, 6 heterocyclics, 2 hydrocarbons, and 1 acid and 1 ether.

[0053] In order to further compare the differences between the volatile components in different wolfberry purees, the Gallery Plot software provided by GC-IMS was used to draw fingerprints of different wolfberry puree samples. Fingerprints can intuitively reflect the different compounds in different wolfberry purees. According to the peak area of ​​each substance in the fingerprint of different wolfberry puree samples, chemometric analysis was performed to obtain the characteristic markers of the volatile components of different wolfberry purees, that is, the characteristic flavors.

[0054] The characteristic flavors of NFC wolfberry puree include 2-hexenal (monomer), 2-ethyl-6-methylpyrazine, (E,E)-2,4-heptadienal, propyl acetate, (E)-2-heptenal, 3-methyl-2-pentanone, trans-2-hexenol, methyl acetate, 2-n-butylfuran, 3-hexanone (monomer) and ethyl acetate;

[0055] The characteristic flavor of FC wolfberry puree includes heptaldehyde (dimer), 2-n-pentylfuran, isobutylaldehyde, 2-methyl-3-furanthiol, isovaleraldehyde, 1-penten-3-one and phellandrene;

[0056] The characteristic flavor of wolfberry dried fruit rehydrated puree includes tetrahydrofuran, 3-hydroxy-2-butanone, 4-methyl-1-pentanol (dimer), pyridine, butyl hexanoate, 4-methyl-2-pentanone, isopentanol, propionic acid, ethyl acetoacetate, 4-methyl-1-pentanol (monomer), furfural (monomer), isovaleraldehyde, 2-heptanone, n-butyraldehyde and 2 unidentified substances.

[0057] (3) The partial least squares-discriminant analysis method was used to analyze the variable projection importance values ​​of different types of volatile components, and the characteristic markers of volatile components were screened out according to the variable projection importance values; the details are as follows:

[0058] SIMCA 14.1 was used for principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) to establish an identification model for the flavor quality of wolfberry puree. As a supervised discriminant analysis statistical method, PLS-DA divides variable data and classification information into two sets of data sets, and uses projection and discriminant calculations to mine inter-group differences with the help of grouping information, thereby distinguishing each group of samples. In order to reduce the risk of model overfitting, the number of potential variables in PLS-DA is determined by internal cross validation (Cross Validation, CV). When constructing the model, one sample is used as a validation set, and the remaining samples are used as training sets. Each sample is used as a validation set in turn, and the prediction residual error sum of squares (PRESS) of all samples is recorded. This is the leave-one-out method; the leave-n method is to take multiple samples as a group, and remove one group as a validation set during each training. The leave-one-out method and the leave-n method are two forms of CV. The present invention adopts the leave-n method, that is, 8 samples used for NFC wolfberry puree, FC wolfberry puree and wolfberry dry fruit rehydrated puree are divided into 8 groups for 8 cross validations, and the prediction ability parameter (Q 2 ) and goodness of fit value (R 2 ) represent the prediction ability and explanation effect of the model, which are important indicators for evaluating model performance. 2 During cross validation, it can be calculated by the following formula:

[0059]

[0060] Among them, PRESS is the residual sum of squares, y is the actual value of the model, is the model's predicted value.

[0061] According to the formula, Q 2 The larger the value, the stronger the model's predictive ability. 0.4 is considered the critical value of whether the model is effective or not. 2 The closer the value is to 1, the stronger the prediction ability is. 2 It's Q 2 The value before cross validation, therefore, R 2 Not as important as Q in model quality evaluation 2 ,like Figure 6 The cross-validation results of different wolfberry puree identification models showed that R 2 and Q 2They are 0.9905 and 0.9864 respectively, which proves that the PLS-DA model has a fairly high accuracy in prediction and can effectively explain and predict the differences between samples.

[0062] The identification model of different wolfberry puree flavor substances was constructed by PCA and PLS-DA, which can well explain and predict the differences between samples. By screening out 19 volatile component characteristic markers when the VIP value in the identification model is greater than 1, different types of wolfberry puree can be identified.

[0063] The eight volatile components in NFC wolfberry puree were (E,E)-2,4-heptadienal, 2-ethyl-6-methylpyrazine, 3-hexanone (monomer), 2-hexenal (monomer), ethyl acetate, ethyl isobutyrate, 2-n-butylfuran and (E)-2-heptenal.

[0064] The eight volatile components in FC wolfberry puree were 2-pentylfuran, heliotropin propylene glycol acetal, 2-methylbutanal, isobutyraldehyde, isovaleraldehyde, 2-methyl-3-furanthiol, heptaldehyde (monomer) and phellandrene.

[0065] The three characteristic markers of volatile components in the rehydrated wolfberry puree are n-butyraldehyde, 6-benzylaminopurine and furfural (monomer).

[0066] Figure 1 The three-dimensional spectra of GC-IMS of different wolfberry puree samples, where the X-axis is the ion migration time, the Y-axis is the retention time, and the Z-axis represents the ion peak intensity. Figure 1 It can be seen that the composition of volatile flavor compounds in NFC wolfberry puree, FC wolfberry puree and wolfberry dried fruit rehydrated puree all have different degrees of difference, which is mainly reflected in the position, number and peak intensity of the ion peaks. These differences are the basis for distinguishing them in the present invention. The three-dimensional map is normalized to obtain a two-dimensional top view as shown in Figure 2 As shown in the figure, the horizontal axis is the time of ion migration, the vertical axis is the retention time of gas chromatography, and the left side is the reaction ion peak (RIP). Each point on both sides of this peak represents a volatile substance. The darker the color, the higher the content. Figure 2It can be seen that most of the signals in the wolfberry puree samples appear in the retention time of 100-400s and the drift time of 1.0-2.0. In the NFC wolfberry puree and FC wolfberry puree, some volatile compounds appear between the retention time of 500-700s. This is because the low polarity of these components makes them stay longer on the non-polar column. The types and contents of volatile substances with retention time of 200-300s are significantly reduced or even disappear in the wolfberry dried fruit rehydrated puree, while the concentration of some volatile components increases significantly in 100-200s, forming the characteristic flavor of the wolfberry dried fruit rehydrated puree.

[0067] Using the NIST and IMS databases built into the GC-IMS software, a detailed qualitative study was conducted on the volatile compounds identified in the wolfberry puree samples. In the process, a total of 48 volatile components were identified, and 45 typical volatile flavor compounds were qualitatively identified, including 15 aldehydes, 8 alcohols, 6 ketones, 6 esters, 6 heterocycles, 2 hydrocarbons, 1 acid and 1 ether. In the wolfberry puree samples, aldehydes, ketones and alcohol compounds are the key components of its volatile substances. The carbon chain lengths of the identified volatile compounds are mainly concentrated in C 4 -C 12 Some compounds, due to their high concentration, formed corresponding dimers in the IMS drift tube and generated multiple points or signals.

[0068] In order to further compare the differences between the volatile components in different wolfberry purees, the built-in Gallery Plot software of GC-IMS was used to create fingerprints of different wolfberry puree samples. Each row in the spectrum shows all the signal peaks screened from a certain wolfberry puree sample, and each column represents the signal peaks of the same volatile compound from different wolfberry puree samples. Bright peaks represent higher signal intensity and richer content; darker signals mean lower intensity and lower content. Figure 3 As shown, NFC wolfberry puree, FC wolfberry puree and wolfberry dried fruit rehydrated puree each have a different characteristic flavor area.

[0069] from Figure 3 It can be seen that there are 34 different compounds in different wolfberry purees that can be used as characteristic markers, as follows:

[0070] The characteristic flavor of NFC wolfberry puree is region A, including 11 characteristic substances: 2-hexenal (monomer), 2-ethyl-6-methylpyrazine, (E,E)-2,4-heptadienal, propyl acetate, (E)-2-heptenal, 3-methyl-2-pentanone, trans-2-hexenol, methyl acetate, 2-n-butylfuran, 3-hexanone (monomer) and ethyl acetate;

[0071] Compared with NFC wolfberry puree, the contents of these substances in FC wolfberry puree decreased significantly. Region B is the unique flavor compounds of FC wolfberry puree, including 7 kinds: heptanal (dimer), 2-n-pentylfuran, isobutylaldehyde, 2-methyl-3-furanthiol, isovaleraldehyde, 1-penten-3-one and phellandrene. Most of its flavor compounds are hydrocarbons and heterocyclic compounds, which have less contribution to its aroma.

[0072] Region C is the unique flavor compounds of wolfberry rehydrated puree, with 16 unique flavor compounds, namely tetrahydrofuran, 3-hydroxy-2-butanone, 4-methyl-1-pentanol (dimer), pyridine, butyl hexanoate, 4-methyl-2-pentanone, isopentanol, propionic acid, ethyl acetoacetate, 4-methyl-1-pentanol (monomer), furfural (monomer), isovaleraldehyde, 2-heptanone, n-butyraldehyde and 2 unidentified substances. Among these volatile compounds, alcohol compounds can give wolfberry puree a light aroma, and aldehyde and ketone compounds have fruity and sweet aromas. In addition, the increase of aldehyde and ketone compounds in wolfberry rehydrated puree may be due to the high temperature of wolfberry during drying, which makes some alcohol compounds easy to esterify or oxidize to form ketones and aldehydes.

[0073] The principal component analysis was performed using the data of 48 characteristic volatile compounds screened by fingerprint and 8 different wolfberry puree samples. Figure 4 As shown in the figure, different wolfberry purees are distributed in different quadrants, the first principal component contributes 53.3%, and the second principal component contributes 20.3%, and the overall variance contribution rate reaches 73.6%. Through the PCA score chart, the differences in volatile flavor substances in wolfberry puree samples processed by different methods can be clearly observed. Through principal component analysis, it was found that volatile flavor substances in wolfberry puree samples processed by different methods can be distinguished.

[0074] PLS-DA was used to further analyze the characteristic flavor compounds of different wolfberry puree samples and to construct a flavor quality identification model for different wolfberry purees. PLS-DA is a supervised statistical processing technique. Under the premise of known sample grouping, partial least squares method was used to reduce the dimension of the data, and a regression model was established. At the same time, the regression data of the model was analyzed for discriminability. By introducing grouping variables to compensate for the limitations of PCA, this method can more accurately reflect the differences between groups of samples. Figure 5 The two-dimensional score diagram of the PLS-DA model is shown. Different wolfberry purees are well distinguished, and the subject areas of the three types of wolfberry purees do not overlap with each other. Figure 6 is a permutation test plot. In these data, R 2 The value reached 0.9905, and Q 2The value of is 0.9864, which proves that the PLS-DA model has a fairly high accuracy in prediction and can effectively explain and predict the differences between samples. In order to avoid overfitting of the model, 200 ranking tests are used to evaluate the performance of the model. Figure 6 As shown, R 2 The value of Q is 0.1317. 2 The value of is -0.4574, and the regression line shows a linear upward trend, proving that the model is not overfitted. This shows that the characteristic flavor compound data information of different wolfberry purees show significant differences through PLS-DA analysis, which can be used as a basis to effectively distinguish NFC wolfberry puree, FC wolfberry puree and wolfberry dried fruit rehydrated puree.

[0075] In the PLS-DA model, the contribution of volatile components to the effective differentiation of wolfberry purees processed by different methods can be expressed by the VIP value. The larger the VIP value, the more significant the difference between the variables among the samples. Figure 7 As shown, a total of 19 characteristic markers with VIP>1 were screened out, including: 2-n-pentylfuran, (E,E)-2,4-heptadienal, 2-ethyl-6-methylpyrazine, 3-hexanone (monomer), 2-hexenal (monomer), ethyl acetate, heliotropin propylene glycol acetal, 2-methylbutanal, ethyl isobutyrate, isobutyraldehyde, 2-n-butylfuran, isovaleraldehyde, n-butyraldehyde, 6-benzylaminopurine, 2-methyl-3-furanthiol, heptaldehyde (monomer), (E)-2-heptenal, phellandrene and furfural (monomer).

[0076] The contents of eight volatile substances, including (E,E)-2,4-heptadienal, 2-ethyl-6-methylpyrazine, 3-hexanone (monomer), 2-hexenal (monomer), ethyl acetate, ethyl isobutyrate, 2-n-butylfuran and (E)-2-hexenal, in NFC wolfberry puree were higher than those in the other two purees, indicating that these compounds are heat-sensitive substances and will be lost or decomposed into other substances during drying or evaporation concentration. Among them, (E,E)-2,4-heptadienal, 2-hexenal and (E)-2-hexenal were higher in N The higher content of FC wolfberry puree is consistent with the research results of Gao Yidan on the changes of volatile components in fresh and dried wolfberry fruits. They give NFC wolfberry puree a certain aroma such as fruity and fresh fragrance; 2-n-pentylfuran, heliotropin propanediol acetal, 2-methylbutanal, isobutyraldehyde, isovaleraldehyde, 2-methyl-3-furanthiol, heptaldehyde (monomer) and phellandrene are higher in FC wolfberry puree, which may be new substances produced during the concentration and reconstitution process; furfural (monomer) has the highest content in the rehydrated puree of dried fruits. These compounds are important characteristics for distinguishing NFC wolfberry puree, FC wolfberry puree and wolfberry dried fruit rehydrated puree, and play a key role in their identification.

[0077] It should be noted that Figure 4 , Figure 5 and Figure 7 The purpose is to distinguish the three types of wolfberry puree, so Figure 4 , Figure 5 and Figure 7 It is further proved that the method of the present invention can effectively distinguish wolfberry purees processed in different ways.

[0078] The present invention uses wolfberry puree with different processing methods as raw materials, and analyzes the differences in volatile components based on GC-IMS to identify the processing methods of the wolfberry puree to be tested. Different processing methods will affect the volatile components in the wolfberry puree. NFC wolfberry puree, FC wolfberry puree and wolfberry dried fruit rehydrated puree each have different characteristic flavor regions, which can be well distinguished.

[0079] (4) The wolfberry pulp to be tested is analyzed by gas chromatography-ion mobility spectrometry to obtain the volatile components of the wolfberry pulp to be tested, and the volatile components of the wolfberry pulp to be tested are compared with the characteristic markers of the volatile components to identify the processing method of the wolfberry pulp to be tested, as follows:

[0080] In the subsequent verification process, when 30 unknown wolfberry puree samples were analyzed by gas chromatography-ion mobility spectrometry, a total of 57 volatile flavor compounds were identified, including 16 aldehydes, 8 esters, 7 ketones, 7 alcohols, 4 ethers, 3 acids, 2 hydrocarbons and 10 heterocyclics. The identification model established by the partial least squares method-discriminant analysis method is used for prediction. The identification results of the model are consistent with the wolfberry puree sample type, and the recognition rate reaches 100%, indicating that the identification model of wolfberry puree with different processing methods established by the present invention is effective.

[0081] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0082] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for identifying wolfberry purees processed in different ways, characterized in that: The following steps are involved: The volatile components of the standard samples of wolfberry puree processed in different ways were detected by gas chromatography-ion mobility spectrometry to obtain GC-IMS sample data. GC-IMS software was used to classify the GC-IMS sample data and obtain different types of volatile components; The partial least squares-discriminant analysis method was used to analyze the variable projection importance values ​​of different types of volatile components, and the characteristic markers of volatile components were screened out according to the variable projection importance values. The volatile components of the wolfberry pulp to be tested are analyzed by gas chromatography-ion mobility spectrometry to obtain the volatile components of the wolfberry pulp to be tested, and the volatile components of the wolfberry pulp to be tested are compared with the characteristic markers of the volatile components to identify the processing method of the wolfberry pulp to be tested; The characteristic markers of volatile components of the standard of non-concentrated reduced wolfberry puree are (E,E)-2,4-heptadienal, 2-ethyl-6-methylpyrazine, 3-hexanone, 2-hexenal, ethyl acetate, ethyl isobutyrate, 2-n-butylfuran and (E)-2-hexenal. When the above compounds are simultaneously analyzed in the wolfberry puree to be tested, the processing method is the non-concentrated reduction method. The characteristic markers of volatile components of the standard product of concentrated and reduced wolfberry puree are 2-n-pentylfuran, heliotropin propylene glycol acetal, 2-methylbutyraldehyde, isobutyraldehyde, isovaleraldehyde, 2-methyl-3-furanthiol, heptaldehyde and phellandrene. When the above compounds are simultaneously analyzed in the wolfberry puree to be tested, the processing method is the concentrated reduction method. The characteristic markers of volatile components of the standard sample of wolfberry dried fruit rehydrated puree are n-butyraldehyde, 6-benzylaminopurine and furfural monomers. When the above compounds are analyzed simultaneously in the wolfberry puree to be tested, its processing method is the wolfberry dried fruit rehydration method.

2. The method for identifying wolfberry purees with different processing methods according to claim 1, characterized in that: The method of classification is as follows: According to the retention index of the standard substance in the GC-IMS software and the retention time determined experimentally, the Reporter plug-in, Gallery Plot plug-in, and GC×IMS LibrarySearch software are used to classify the GC-IMS sample data.

3. The method for identifying wolfberry purees with different processing methods according to claim 1, characterized in that: Different classes of volatile components include aldehydes, alcohols, ketones, esters, heterocycles, hydrocarbons, acids, and ethers.

4. The method for identifying wolfberry purees with different processing methods according to claim 1, characterized in that: The variables corresponding to the characteristic markers of volatile components were screened out and their projection importance values ​​were greater than 1.

5. The method for identifying wolfberry purees with different processing methods according to claim 1, characterized in that: Wolfberry puree with different processing methods includes non-concentrated and reconstituted wolfberry puree, concentrated and reconstituted wolfberry puree and wolfberry dried fruit rehydrated puree.

6. The method for identifying wolfberry purees with different processing methods according to claim 1, characterized in that: The detection conditions of gas chromatography are as follows: MXT-5 gas chromatography column, column temperature of 40°C; carrier gas is nitrogen with a purity of 99.99%, and the initial flow rate of the carrier gas flow system is 2mL / min, maintained for 2min, 15mL / min maintained for 10min, the flow rate is increased to 100mL / min and maintained for 20min, and the flow rate is increased to 150mL / min for 30min.

7. The method for identifying wolfberry purees with different processing methods according to claim 1, characterized in that: The ion mobility spectrometry conditions were as follows: temperature was 45°C, E1 drift gas flow rate was 150 mL / min, and the drift gas was nitrogen with a purity of 99.99%.

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