Determination method for volatile flavor substances of waxberries from different producing areas and application of determination method

Abstract

The invention relates to the technical field of waxberry flavor detection, in particular to a method for determining volatile flavor substances of waxberries from different producing areas and application of the method. The method comprises the following steps: firstly, enriching volatile flavor substances in waxberry samples to be detected from different producing areas by using a headspace solid-phase microextraction technology; analyzing by using a gas chromatography-mass spectrometry system to obtain qualitative and quantitative data of the volatile flavor substances; analyzing by using a gas chromatography-ion mobility spectrometry combined system to obtain fingerprint spectrum data of the volatile flavor substances; and finally, performing multivariate statistical analysis on the basis of qualitative and quantitative data of the volatile flavor substances and fingerprint spectrum data, and determining composition characteristics and differences of the volatile flavor substances in the waxberry samples to be detected from different producing areas. Through cooperative application of multiple analysis technologies, the coverage degree, accuracy and distinguishing capacity of waxberry volatile flavor substance detection are improved, and flavor characteristics of waxberries from different producing areas can be effectively distinguished.

Description

Technical Field

[0001] This invention relates to the field of bayberry flavor detection technology, and in particular to a method for determining volatile flavor compounds in bayberries from different origins and its application. Background Technology

[0002] Waxberry, a subtropical fruit with significant economic value, is widely cultivated. Visually, the waxberry fruit is spherical, with colors ranging from deep red to purplish-red, and its surface is covered with small granules. In terms of taste, waxberries are known for their sweet and sour flavor. Nutritionally, waxberries are rich in vitamin C, fiber, and other nutrients, offering certain health benefits. They can promote digestion and enhance immunity. Waxberries are a berry fruit with representative flavor characteristics, and the composition of their volatile flavor compounds is an important indicator for evaluating their quality and origin. However, waxberries from different origins have different flavors, and flavor is a crucial indicator of their freshness and quality. Existing research shows that waxberries contain a wide variety of volatile components, including aldehydes, alcohols, esters, terpenes, and ketones, but the composition of volatile flavor compounds varies significantly between waxberries from different origins and at different stages of ripeness. Currently, most existing technologies use a single detection method to analyze the volatile flavor compounds of bayberry. These methods generally have the following shortcomings: severe co-elution of compounds, incomplete qualitative analysis; low abundance or highly polar volatile flavor compounds are easily missed; it is difficult to achieve both high-resolution qualitative analysis and rapid fingerprint identification; and the coverage of the volatile characteristics of bayberry from different origins is insufficient.

[0003] Therefore, there is an urgent need for a method that can broadly, comprehensively, and accurately determine the composition of volatile flavor compounds in bayberries in order to overcome the limitations of existing technologies. Summary of the Invention

[0004] To address the aforementioned problems, the purpose of this invention is to provide a method for determining the volatile flavor compounds of bayberries from different origins and its application. This invention achieves high coverage, high accuracy, and high repeatability in the identification of volatile components in bayberries through the synergistic use of multiple flavor analysis techniques, thereby obtaining a more complete picture of the volatile flavor compounds in bayberries.

[0005] Headspace solid-phase microextraction (HS-SPME) was used to enrich volatile flavor compounds in bayberry samples, effectively reducing matrix interference and improving the detection sensitivity and qualitative accuracy of volatile flavor compounds. This method eliminates the need for organic solvents, reducing environmental pollution and avoiding solvent interference in the detection of volatile flavor compounds. Therefore, this study used gas chromatography-mass spectrometry (GC-MS) and gas chromatography-ion mobility spectrometry (GC-IMS) combined with SPME to analyze the flavor compounds of bayberries from different origins, enabling more accurate quantitative and qualitative analysis, efficiently obtaining the most complete results on flavor compounds, and identifying the differences in flavor compounds among bayberries from different origins.

[0006] The objective of this invention can be achieved through the following technical solutions: The first objective of this invention is to provide a method for determining the volatile flavor compounds of bayberries from different origins, comprising the following steps: (S1) Headspace solid-phase microextraction was used to enrich volatile flavor compounds in pretreated bayberry samples from different origins. (S2) The volatile flavor compounds enriched in step (S1) were analyzed using a gas chromatography-mass spectrometry (GC-MS) system to obtain qualitative and quantitative data of the volatile flavor compounds. (S3) The volatile flavor compounds enriched in step (S1) were analyzed using a gas chromatography-ion mobility spectrometry (GC-IMS) system to obtain fingerprint data of the volatile flavor compounds. (S4) Based on the qualitative and quantitative data of volatile flavor compounds obtained in step (S2) and the fingerprint data of volatile flavor compounds obtained in step (S3), multivariate statistical analysis was performed to determine the compositional characteristics and differences of volatile flavor compounds in bayberry samples from different origins.

[0007] In one embodiment of the present invention, the preprocessing in step (S1) specifically includes the following: The bayberry fruits were processed in sequence as follows: removing impurities, freezing, thawing, crushing, and juicing.

[0008] In one embodiment of the present invention, in step (S1), headspace solid-phase microextraction is performed in a closed headspace container; During the enrichment process, o-dichlorobenzene was used as an internal standard, the temperature was 40-50 °C, and the time was 25-35 min.

[0009] Preferably, during the enrichment process, o-dichlorobenzene is used as an internal standard, the temperature is 45 °C, and the time is 30 min.

[0010] In one embodiment of the present invention, the chromatographic conditions in step (S2) are as follows: The polar chromatographic column was an HP-INNOWAX quartz capillary column with an injection port temperature of 240–250 °C. A programmed temperature ramp was used: initial temperature 35–40 °C, held for 1–2 min, ramped at 5–10 °C / min to 150–160 °C, held for 1–2 min, then ramped at 5–10 °C / min to 240–250 °C, held for 4–5 min. The carrier gas was high-purity He with a flow rate of 10–15 mL / min, using a split injection mode of 5:1 and a total flow rate of 5–10 mL / min. The specific mass spectrometry conditions are as follows: Ion source temperature 220~230 ℃, quadrupole temperature 140~150 ℃, ionization energy 60~70 eV, scan range m / z 50~550 amu, solvent delay 5~10 min, ionization method electron bombardment, electron energy 70~80 eV, GC-MS interface temperature 240~250 ℃.

[0011] Preferably, the chromatographic conditions are as follows: The polar chromatographic column was an HP-INNOWAX quartz capillary column (60m×0.25mm×0.25μm), with an injection port temperature of 250℃. The temperature was programmed, starting at 40℃ and holding for 2 min, then increasing to 160℃ at 5℃ / min and holding for 1 min, and finally increasing to 250℃ at 10℃ / min and holding for 4 min. The carrier gas was high-purity He, with a flow rate of 12 mL / min, using a split injection mode of 5:1 and a total flow rate of 10 mL / min. The specific mass spectrometry conditions are as follows: Ion source temperature 230 ℃, quadrupole temperature 150 ℃, ionization energy 70 eV, scan range m / z 50~550 amu, solvent delay 6 min, ionization mode electron impact (EI), electron energy 70 eV, GC-MS interface temperature 250 ℃.

[0012] In one embodiment of the present invention, the qualitative analysis in step (S2) is as follows: The mass spectrometry data were deconvolved using Amdis software to separate co-eluting chromatographic peaks. The identities of volatile flavor compounds were determined by combining search results from the NIST 2011 mass library and the Amdis mass library, along with retention index (RI) values ​​and manual searching. For quantitative analysis, the internal standard method is used for calculation.

[0013] In one embodiment of the present invention, the chromatographic conditions in step (S3) are as follows: Without splitting, the initial flow rate is 2-3 mL / min for 1-2 min; then the flow rate is increased to 10-15 mL / min over 5-10 min, to 100-120 mL / min over 10-15 min, and to 140-150 mL / min over the last 10-20 min; The ion mobility spectra are as follows: The drift gas is high-purity nitrogen, with a flow rate of 140~150 mL / min and a temperature of 40~50 ℃.

[0014] Preferably, the chromatographic conditions are as follows: Without splitting, the initial flow rate was 2 mL / min for 2 min; then the flow rate was increased to 10 mL / min over 8 min, to 100 mL / min over 10 min, and to 150 mL / min over the last 15 min. The ion mobility spectra are as follows: The drift gas was high-purity nitrogen, with a flow rate of 150 mL / min and a temperature of 45 ℃.

[0015] In one embodiment of the present invention, in step (S3), the Gallery Plot plugin is used to automatically generate comprehensive analytical peak fingerprint spectra of bayberry samples from different origins.

[0016] In one embodiment of the present invention, the multivariate statistical analysis includes the correlation and differences between qualitative and quantitative data of volatile flavor compounds and fingerprint data of volatile flavor compounds.

[0017] The second objective of this invention is to provide a method for determining the volatile flavor compounds of bayberries from different origins, and its application in identifying the origin of bayberries from different regions.

[0018] Compared with the prior art, the present invention has the following beneficial effects: (2) The method for determining volatile flavor compounds of bayberries from different origins provided by the present invention can simultaneously detect aldehydes, alcohols, esters, terpenes, ketones and other trace volatile flavor compounds, significantly increasing the number of volatile flavor compounds identified. At the same time, the present invention uses GC-IMS to construct a volatile fingerprint spectrum of bayberries, enabling rapid differentiation and traceability analysis of bayberries from different origins.

[0019] (2) The method for determining volatile flavor substances of bayberry from different origins provided by the present invention is applicable to bayberry samples from different origins, varieties and processing states. The present invention improves the coverage, accuracy and distinguishing ability of volatile flavor substance detection of bayberry through the synergistic application of multiple analytical techniques, and can effectively distinguish the flavor characteristics of bayberry from different origins. Attached Figure Description

[0020] Figure 1 A bar chart showing the accumulation of volatile components in bayberries from different origins; Figure 2 Heat maps of volatile flavor compounds of terpenoids in bayberries from different origins; Figure 3 Venn diagram of volatile flavor compounds common to bayberries from different origins; Figure 4 Topographic maps showing the volatile fingerprint spectra of bayberries from different origins; Figure 5Fingerprint spectral data of volatile components in bayberries from different origins; Figure 6 PCA diagrams of volatile flavor compounds in bayberries from different origins, measured by GC-MS. Figure 7 PCA diagram of volatile flavor compounds in bayberries from different origins, measured by GC-IMS. Detailed Implementation

[0021] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0022] Unless otherwise specified, all reagents used in the following embodiments are commercially available reagents, and all detection methods and techniques used are conventional detection methods and techniques in the art.

[0023] Example 1 This embodiment provides a method for determining the volatile flavor compounds of bayberries from different origins, specifically including the following steps: (S1) The bayberries purchased from Cixi, Taizhou, Yuyao, Honghe and Fugong were cleaned of impurities, then packaged and sealed and stored in a freezer at -18 ℃; before use, the bayberries were taken out of the freezer, thawed at room temperature and juiced; bayberry samples from different origins were obtained for testing. (S2) SPME method: Take 2 g of bayberry samples from different origins and put them into a 20 mL headspace vial. Add 10 μL of o-dichlorobenzene as an internal standard. After equilibration for 15 min, insert the aged SPME extraction needle into the sample vial and heat in a 45 ℃ water bath for 30 min. Pull the SPME extraction needle with the fiber head pulled back out of the sample vial, then insert the SPME extraction needle into the gas chromatograph injection port and desorb at 250 °C for 10 min to complete the enrichment of volatile flavor substances. (S3) The volatile flavor compounds enriched in step (S2) were analyzed using a gas chromatography-mass spectrometry system to obtain qualitative and quantitative data of the volatile flavor compounds. The gas chromatography (GC) conditions were as follows: a polar HP-INNOWAX quartz capillary column (60 m × 0.25 mm × 0.25 μm), an injection port temperature of 250 ℃, and a programmed temperature ramp: an initial temperature of 40 ℃, held for 2 min, ramped to 160 ℃ at 5 ℃ / min, held for 1 min, and then ramped to 250 ℃ at 10 ℃ / min, held for 4 min; the carrier gas was high-purity He, with a carrier gas flow rate of 12 mL / min, a split injection mode of 5:1, and a total flow rate of 10 mL / min. Mass spectrometry (MS) conditions: ion source temperature 230 °C, quadrupole temperature 150 °C, ionization energy 70 eV, scan range m / z 50~550 amu, solvent delay 6 min, ionization mode electron impact (EI), electron energy 70 eV, GC-MS interface temperature 250 °C.

[0024] The data processing is as follows: Qualitative analysis: Under the same sample analysis conditions, for n-alkanes C7-C 30 Standard samples were analyzed to calculate their retention indices: the mass spectrometry data were deconvolved using Amdis software to separate co-eluting chromatographic peaks; the results of searches in the NIST 2011 mass spectrometry library and the Amdis mass spectrometry library, along with retention index (RI) values, and supplemented by simultaneous searches at https: / / webbook.nist.gov / chemistry / cas-ser / , were used to identify the volatile flavor compounds.

[0025] Quantitative analysis: The content of each different volatile flavor compound was determined using the internal standard method with o-dichlorobenzene as the internal standard. The content calculation formula is as follows: In the formula: Wi represents the mass concentration of the volatile component to be tested (μg / g); Cs represents the concentration of the internal standard (μg / mL); Vs represents the volume of the internal standard added (μL); m represents the mass of the sample weighed (g); APi represents the peak area of ​​the volatile component (Area Pct); APs represents the peak area of ​​the internal standard (Area Pct). Identification of key aroma compounds: First, GC-MS analysis was performed on bayberries from five different production areas. The obtained data were then analyzed using the Aroma Activity Value (OAV) method to screen for volatile compounds with an OAV > 1. Compounds with an OAV > 1 were considered to contribute to the formation of characteristic aromas, and the higher the OAV, the more likely they were to become key aroma compounds. The OAV calculation formula is as follows: Where: Wi represents the mass concentration of the volatile component to be tested / (μg / g); DT represents the threshold of the volatile component in water / (ug / g); Volatile flavor compounds of bayberries from different origins were analyzed by GC-MS. The GC-MS results were qualitatively analyzed using the NIST20 spectral library integrated into the mass spectrometer. The calculated retention index (RI) was compared with RIs obtained using the same or equivalent chromatographic columns reported in the literature. The chemical structure with the highest MS similarity and RI closeness was considered the best identification result. The internal standard method was used to quantitatively calculate the content of different volatile flavor compounds in bayberries from different origins. Experimental data are expressed as mean ± standard deviation. Data processing and statistical analysis were performed using Excel 2019, and graphs were generated using Origin 2025 software.

[0026] Results analysis: A total of 178 volatile flavor compounds were isolated and identified from bayberries from five different production areas. The content and quantity varied among the samples from the five areas: 69 from Cixi bayberries, 91 from Fugong bayberries, 93 from Honghe bayberries, 94 from Taizhou bayberries, and 80 from Yuyao bayberries. The compounds included 20 aldehydes, 35 alcohols, 40 esters, 44 terpenes, 4 acids, 18 ketones, and 17 others (aromatic hydrocarbons, furans, ethers, etc.). Among the volatile components, those with higher content were cis-3-nonen-1-ol, dextrorotatory terpene, ocimene, (-)-isoeugenol, caryophyllene, 2-nonanone, and caryophyllein. Figure 1 It can be observed that the acid content of bayberries is generally low, while the content of terpenes is the largest.

[0027] Terpenes are the main flavor compounds in bayberries and play a crucial role in their flavor profile. Through... Figure 2 It can be observed that caryophyllene, a key flavor component in bayberry, belongs to the bicyclic sesquiterpenoid class of compounds. This compound is known for its unique spicy, woody, and clove-like aroma, and its content in bayberry is as high as 80%. A total of 13 substances were found in bayberries from five different producing areas: β-pinene, myrcene, dextrorotatory terpene, γ-terpinene, styrene, terpinene, β-boronene, caryophyllene, α-rutinophyllene, α-guargenene, geraniolene, β-serinene, and α-farnesene.

[0028] The bayberries from the five production areas share 23 volatile flavor compounds, namely: natural nonanal, trans-3-hexen-1-ol, octanol, cis-3-nonen-1-ol, methyl nonenoate, β-pinene, myrcene, dextrorotatory terpene, γ-terpinene, styrene, terpinene, β-boronene, caryophyllene, α-ursulphene, α-guargenene, geraniol, β-serrinene, α-farnesene, acetic acid, methyl heptenone, 2-nonanone, menthol, and caryophyllein. Figure 3 ).

[0029] (S4) The volatile flavor compounds enriched in step (S2) are analyzed using a gas chromatography-ion mobility spectrometry system to obtain fingerprint data of the volatile flavor compounds. 1.0 mL of bayberry juice was added to a 20 mL headspace vial and heated at 50 °C for 15 min. Then, at 85 °C, 500 μL of headspace gas sample was automatically injected into the injector using a splitless syringe. 99.999% pure nitrogen was used as the carrier gas, and the flow rate was controlled according to the following procedure: an initial flow rate of 2 mL / min for 2 min to separate difficult-to-separate compounds; then increasing the flow rate to 10 mL / min over 8 min, 100 mL / min over 10 min, and finally 150 mL / min over the last 15 min, allowing for rapid analysis of samples with different characteristics at different flow rates; the entire detection process took 35 min. The analytes were eluted and separated at 60 °C, and subsequently ionized in an ion mobility spectrometry (IMS) ionization chamber equipped with a 6.5 keV positive ion mode tritium ionization source. High-purity nitrogen (99.999% purity) was set as the drift gas for IMS, the flow rate was set to 150 mL / min, and the drift tube temperature was kept constant at 45℃. Qualitative analysis of volatile compounds was achieved by comparing the retention index (RI) of standard substances in the GC-IMS NIST library with the time it takes for ions to reach the detector through the drift tube (drift time, in milliseconds).

[0030] The data processing is as follows: The instrumental analysis software includes Vocal, three add-on components, and GC×IMS Library Search, enabling multi-dimensional sample analysis. The LAV tool is used to view analytical spectra, where each point represents a volatile organic compound (VOC), while the GC×IMS library search employs a two-dimensional cross-qualitative method for qualitative analysis. Excel 2019 is used for data processing and statistical analysis.

[0031] Results analysis: A total of 54 identical volatile flavor compounds were isolated and identified from bayberries from 5 different production areas. The contents of different volatile flavor compounds varied. The types of compounds included 11 aldehydes, 12 alcohols, 6 esters, 2 terpenes, 3 acids, 8 ketones, and 12 others (aromatic hydrocarbons, furans, pyrazines, etc.).

[0032] Figure 4 This is a difference comparison model used to analyze bayberry samples from different origins. In this model, the points on the right represent volatile compounds in the samples, which mainly appear in the drift time range of 1.0 to 2.0 and the retention time range of 200 to 700 seconds.

[0033] In the drift time range of 1.0 to 1.5 seconds, the concentration of volatile flavor compounds in Honghe bayberries was significantly higher than that in the other four samples. However, in the retention time range of 600–700 seconds, the concentration of volatile flavor compounds gradually decreased in bayberries from different origins. To identify these differential compounds, a comprehensive analysis of the combined volatile characteristics of different samples is required, which typically involves in-depth statistical analysis.

[0034] To investigate the changes in volatile flavor compounds of bayberries from different origins, comprehensive peak fingerprint spectra of bayberry samples from different origins were automatically generated using the Gallery Plot plugin (see...). Figure 5 In these spectra, each row represents all peaks selected from a single sample, and each column represents peaks of the same volatile compound from bayberries from different origins. Each point in the spectrum represents a volatile flavor compound, and its color intensity reflects the concentration of that compound; brighter colors indicate higher concentrations. This method allows for comparison of the differences in volatile compound content between different samples. Figure 5 As shown, the fingerprint spectrum provides a convenient way to gain a deeper understanding of the details of each volatile flavor compound, with all detected volatile flavor substances distributed in different regions of the spectrum.

[0035] from Figure 5 The results show that the five different origins of bayberries generally have higher levels of citronellol (waxy, rose-like aroma), linalool (citrus blossom, sweet rose aroma), heptanal (aldehyde, fatty aroma), and 2-ethylpyrazine (peanut butter, nutty, roasted cocoa, woody aroma). Among the five origins, Fugong bayberries have the highest total peak intensity, followed by Honghe bayberries, and Cixi bayberries have the lowest. The content of different volatile components varies significantly among the different origins. In Honghe bayberries, the content of bornyl acetate, n-octanal, 2-acetylpyrrole, 3-methylthiopropanol, o-xylene, 2-heptanone, and 2-methylbutyric acid is higher than in other origins. In Cixi bayberries, the content of furanone, phenylacetaldehyde, 2-acetylfuran, 5-nonanone, and propyl hexanoate is higher than in the other four origins, but the content of heptanal, a volatile substance, is lower than in the other four origins. In the waxberries from Fugong, the contents of trans-2-octenal, 2-acetylpyrazine, (E,E)-2,4-heptadienal, 1-octen-3-one, benzaldehyde, 5-methylfurfural, 2-hexanol, and 3-methylthiopropional were higher than those from other origins. This result demonstrates that the volatile flavor compounds in waxberries from the five origins showed different variations in GC-IMS analysis, indicating significant differences in their content.

[0036] (S5) Based on the qualitative and quantitative data of volatile flavor compounds obtained in step (S3) and the fingerprint data of volatile flavor compounds obtained in step (S4), multivariate statistical analysis was performed to determine the compositional characteristics and differences of volatile flavor compounds in bayberry samples from different origins.

[0037] Principal component analysis (PCA) was used for multivariate statistical analysis (including the correlation and differences between qualitative and quantitative data of volatile flavor compounds and fingerprint data of volatile flavor compounds). The data processing is as follows: The content data of volatile flavor compounds were processed and statistically analyzed using Excel 2019, and PCA plots were drawn using Origin 2025 software.

[0038] Results analysis: pass Figure 6 It can be observed that the cumulative contribution rate of PC1 (38.6%) and PC2 (22.3%) is 60.9%, and the factors of bayberries from the five production areas are relatively clustered, which is sufficient to prove that there is a certain similarity among their volatile flavor substances.

[0039] pass Figure 7 It can be observed that in the GC-IMS test results, the cumulative contribution rate of PC1 (40.0%) and PC2 (24.6%) is 64.6%, indicating that the PCA model is the optimal model and is sufficient to explain the similarity among the five bayberry varieties. The figure shows that the five bayberry varieties are located close to each other, indicating that their compound contents are relatively similar and correlated. Moreover, the factors of bayberries from each origin are relatively clustered, indicating that GC-IMS can better distinguish the bayberries from the five origins.

[0040] In summary, the study found 20 volatile flavor compounds that were detected by both GC-MS and GC-IMS, and the volatile flavor compounds of bayberries from the five production areas showed a certain degree of similarity.

[0041] In summary, the instrumental method described in this invention, combined with PCA, can better distinguish the changes in volatile flavor components and their contents, as well as flavor-differentiating components, of bayberries from different origins. Moreover, it has a wider range of reproducible results, higher analytical sensitivity, better accuracy, and good repeatability and reproducibility.

[0042] The above description of the embodiments is provided to enable those skilled in the art to understand and use the invention. It will be apparent to those skilled in the art that various modifications can be made to these embodiments, and the general principles described herein can be applied to other embodiments without inventive effort. Therefore, the present invention is not limited to the above embodiments, and any improvements and modifications made by those skilled in the art based on the interpretation of the present invention, without departing from the scope of the invention, should be within the protection scope of the present invention.

Claims

1. A method for determining the volatile flavor compounds of bayberries from different origins, characterized in that, Includes the following steps: (S1) Headspace solid-phase microextraction was used to enrich volatile flavor compounds in pretreated bayberry samples from different origins. (S2) The volatile flavor compounds enriched in step (S1) were analyzed using a gas chromatography-mass spectrometry system to obtain qualitative and quantitative data of the volatile flavor compounds. (S3) The volatile flavor compounds enriched in step (S1) are analyzed using a gas chromatography-ion mobility spectrometry system to obtain fingerprint data of the volatile flavor compounds. (S4) Based on the qualitative and quantitative data of volatile flavor compounds obtained in step (S2) and the fingerprint data of volatile flavor compounds obtained in step (S3), multivariate statistical analysis was performed to determine the compositional characteristics and differences of volatile flavor compounds in bayberry samples from different origins.

2. The method for determining volatile flavor compounds in bayberries from different origins according to claim 1, characterized in that, In step (S1), the preprocessing is specifically as follows: The bayberry fruits were processed in sequence as follows: removing impurities, freezing, thawing, crushing, and juicing.

3. The method for determining volatile flavor compounds in bayberries from different origins according to claim 1, characterized in that, In step (S1), headspace solid-phase microextraction is performed in a closed headspace container; During the enrichment process, o-dichlorobenzene was used as an internal standard, the temperature was 40-50 °C, and the time was 25-35 min.

4. The method for determining volatile flavor compounds in bayberries from different origins according to claim 3, characterized in that, During the enrichment process, o-dichlorobenzene was used as an internal standard, the temperature was 45 ℃, and the time was 30 min.

5. The method for determining volatile flavor compounds in bayberries from different origins according to claim 1, characterized in that, In step (S2), the chromatographic conditions are as follows: The polar chromatographic column was an HP-INNOWAX quartz capillary column with an injection port temperature of 240–250 °C. A programmed temperature ramp was used: initial temperature 35–40 °C, held for 1–2 min, ramped at 5–10 °C / min to 150–160 °C, held for 1–2 min, then ramped at 5–10 °C / min to 240–250 °C, held for 4–5 min. The carrier gas was high-purity He with a flow rate of 10–15 mL / min, using a split injection mode of 5:1 and a total flow rate of 5–10 mL / min. The specific mass spectrometry conditions are as follows: Ion source temperature 220~230 ℃, quadrupole temperature 140~150 ℃, ionization energy 60~70 eV, scan range m / z 50~550 amu, solvent delay 5~10 min, ionization method electron bombardment, electron energy 70~80 eV, GC-MS interface temperature 240~250 ℃.

6. The method for determining volatile flavor compounds in bayberries from different origins according to claim 5, characterized in that, In step (S2), the qualitative analysis is as follows: The mass spectrometry data were deconvolved using Amdis software to separate the co-eluting chromatographic peaks; the identities of volatile flavor compounds were determined by combining the search results of the NIST 2011 mass spectrometry library and the Amdis mass spectrometry library with the retention index values. For quantitative analysis, the internal standard method is used for calculation.

7. The method for determining volatile flavor compounds in bayberries from different origins according to claim 1, characterized in that, In step (S3), the chromatographic conditions are as follows: Splitless flow, the initial flow rate is 2-3 mL / min for 1-2 min; then the flow rate is increased to 10-15 mL / min over 5-10 min, to 100-120 mL / min over 10-15 min, and to 140-150 mL / min over the last 10-20 min; The ion mobility spectra are as follows: The drift gas is high-purity nitrogen, with a flow rate of 140~150 mL / min and a temperature of 40~50 ℃.

8. The method for determining volatile flavor compounds in bayberries from different origins according to claim 7, characterized in that, In step (S3), the Gallery Plot plugin is used to automatically generate comprehensive analytical peak fingerprint spectra of bayberry samples from different origins.

9. The method for determining volatile flavor compounds in bayberries from different origins according to claim 1, characterized in that, In step (S4), multivariate statistical analysis is performed using principal component analysis. The multivariate statistical analysis includes the correlation and differences between qualitative and quantitative data of volatile flavor compounds and fingerprint data of volatile flavor compounds.

10. The application of the method for determining the volatile flavor compounds of bayberries from different origins as described in any one of claims 1 to 9 in identifying the origins of bayberries from different origins.

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