Method for identifying aging years of pericarpium citri reticulatae

Abstract

The invention provides a dried orange peel aging year identification method, which is characterized in that volatile components in dried orange peel of different aging years are detected by combining an electronic nose with an HS-GC-MS technology, and data processing analysis is carried out by combining principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), clustering analysis and aroma activity value (OAV). The method comprises the following steps: screening differential components and key aroma components in a dried orange peel aging process, exploring the difference among different aging years, finally determining a target component, and then establishing a discrimination model according to different aging years and the content of the target component changing along with the different aging years; and obtaining the content of the target component of the dried orange peel, and inputting the content into the discrimination model to obtain the aging year of the dried orange peel, thereby realizing nondestructive, rapid and accurate identification of the aging year of the dried orange peel.

Description

Technical Field

[0001] The invention belongs to the technical field of Chinese medicinal material identification, and particularly relates to a method for identifying the aging year of tangerine peel. Background Art

[0002] Tangerine peel (Chentouhong) is the dried and mature peel of the tangerine plant and its cultivated varieties of the Rutaceae family. The tangerine peel from Guangdong is the best, and the quality of Guangdong tangerine peel is the best. It has the effects of regulating Qi and strengthening the spleen, drying dampness and resolving phlegm.

[0003] The aging year is an important indicator for its quality evaluation. There are often phenomena such as inferior products being sold as good ones and fake products being sold as real ones in the market. The identification methods of different years of tangerine peel often include identification of medicinal material appearance, gas chromatography-mass spectrometry (GC-MS), gas phase-ion mobility spectrometry (GC-IMS), high performance liquid chromatography (HPLC), ultra-high performance liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC-Q-TOF-MS), targeted mass spectrometry metabolomics, near-infrared spectroscopy (NIRS), hyperspectral imaging technology (HSI), multispectral imaging technology (MSI), etc. The volatile components in tangerine peel can not only objectively reflect the flavor characteristics, but also are one of its important quality indicators.

[0004] At present, the quality analysis of tangerine peel is mainly carried out through the extraction of volatile oil for detection and identification. However, the extraction process of volatile oil is easily affected by external conditions and is time-consuming, resulting in low detection accuracy. Summary of the invention

[0005] Based on this, a method for identifying the aging year of tangerine peel is provided in an embodiment of the present invention, which aims to identify the aging year of tangerine peel quickly, simply and sensitively without loss.

[0006] The embodiment of the present invention provides a method for identifying the aging year of tangerine peel, the method comprising: The tangerine peels of different aging years are detected by an electronic nose at room temperature to obtain the odor information of the tangerine peels of different aging years, and the odor information is used to provide direction for subsequent HS-GC-MS analysis; The dried tangerine peels of different aging years were tested by HS-GC-MS under preset conditions to obtain total ion current graphs, and the relative percentage content of each component was calculated based on the total ion current graphs; The relative percentage content of each component is integrated, and the integration results are qualitatively analyzed by mass spectrometry of the standard database according to the mass spectrum of each peak, and the volatile components with a matching degree greater than a preset value are screened out; The volatile components were used as dependent variables and different years were used as independent variables to conduct unsupervised PCA analysis and OPLS-DA analysis to screen the differential volatile components of tangerine peels from different aging years; determining whether the differentiated volatile components are consistent with the odor information; If it is determined that the differentiated volatile components are consistent with the odor information, cluster analysis is performed on the differentiated volatile components, and it is determined whether the results of the cluster analysis are consistent with the results of the unsupervised PCA analysis and the OPLS-DA analysis; If the results of the cluster analysis are judged to be consistent with the results of the unsupervised PCA analysis and the OPLS-DA analysis, the aroma activity value of each differentiated volatile component is calculated, and the target component among the differentiated volatile components is determined based on the aroma activity value; According to different aging years and the content of target components that change with different aging years, a discriminant model is established; The content of the target component of the dried tangerine peel is obtained and input into the discrimination model to obtain the aging year of the dried tangerine peel.

[0007] Furthermore, in the step of detecting tangerine peel of different aging years by using an electronic nose at room temperature, 0.5 g of tangerine peel sample powder of different aging years is weighed respectively, the tangerine peel sample powder is sieved through a 50-mesh sieve, placed in a 40 mL electronic nose sample bottle, left to stand so that the headspace bottle is filled with sample gas, and detected by using an electronic nose at room temperature, wherein the cleaning time is 180 s, the air intake speed is 0.6 L / min, the detection time is 120 s, the injection volume is 10 mL, and the parallel determination is performed 3 times.

[0008] Furthermore, the odor information includes aromatic compound information, nitrogen oxide information, sulfide information, terpenoid information, ester information, sterol information, triterpenoid information, aliphatic hydrocarbon oxygen-containing derivative information, amine information, hydrogen information, furan information, volatile organic compound information, ethylene information, lactone information and pyrazine information.

[0009] Furthermore, in the step of detecting tangerine peel of different aging years by HS-GC-MS under preset conditions, 0.5 g of tangerine peel sample powder of different aging years is weighed respectively, the tangerine peel sample powder is sieved through a 50-mesh sieve, placed in a 20 mL headspace bottle, sealed with an aluminum cap, and measured in parallel 3 times, wherein the bottle is placed in a sample tray after sealing, the sample bottle heating temperature is 110° C., the quantitative loop temperature is 120° C., the transmission line temperature is 130° C., and the sample bottle equilibration time is 10 min.

[0010] Furthermore, the preset value is 80%.

[0011] Furthermore, in the step of calculating the aroma activity value of each differentiated volatile component, the calculation formula of the aroma activity value is: OAV = concentration of aroma substance in the matrix / detection threshold of the substance in the matrix; Among them, OAV stands for aroma activity value.

[0012] Furthermore, in the step of determining the target component in the differentiated volatile components according to the aroma activity value, when OAV>1, it is determined that the volatile component plays a modifying role in the aroma of tangerine peel red, and when OAV>10, it is determined that the volatile component is the key component of the overall aroma of tangerine peel, that is, the target component.

[0013] Furthermore, in the step of taking the volatile components as dependent variables and different years as independent variables, performing unsupervised PCA analysis and OPLS-DA analysis to screen the differentiated volatile components of tangerine peel in different aging years, SIMCA 14.1 software was used to perform OPLS-DA analysis, and according to SPSS 21.0 one-way ANOVA P<0.05 and VIP value>1, the differentiated volatile components of tangerine peel in different aging years were screened.

[0014] A method for identifying the aging year of tangerine peel provided in an embodiment of the present invention detects volatile components in tangerine peel of different aging years by combining an electronic nose with HS-GC-MS technology, and performs data processing and analysis in combination with principal component analysis (PCA), orthogonal partial least squares method-discriminant analysis (OPLS-DA), cluster analysis and aroma activity value (OAV), screens out differential components and key aroma components in the aging process of tangerine peel, explores the differences between different aging years, and finally determines the target components, then establishes a discrimination model according to different aging years and the content of the target components that change with different aging years; obtains the content of the target components of tangerine peel, and inputs the discrimination model to obtain the aging year of tangerine peel, thereby realizing non-destructive, rapid and accurate identification of the aging year of tangerine peel. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A flowchart of a method for identifying the aging year of tangerine peel provided by an embodiment of the present invention; Figure 2 The radar chart of the electronic nose of tangerine peel samples of different aging years; Figure 3 This is the relative content of volatile components in tangerine peel aged from 2017 to 2023; Figure 4 This is the unsupervised PCA analysis diagram; Figure 5 This is the OPLS-DA analysis diagram; Figure 6 The fingerprints of volatile components in different aging years; Figure 7 VIP diagram of the OPLS-DA model. DETAILED DESCRIPTION

[0016] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0017] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0019] See also Figure 1 , Figure 1 The present invention shows a flowchart of a method for identifying the aging year of tangerine peel provided by an embodiment of the present invention. The method specifically includes steps S01 to S09.

[0020] Step S01, using an electronic nose to detect tangerine peels of different aging years at room temperature to obtain odor information of tangerine peels of different aging years, wherein the odor information is used to provide direction for subsequent HS-GC-MS analysis.

[0021] Specifically, 0.5 g of tangerine peel sample powder from different aging years was accurately weighed, the tangerine peel sample powder was passed through a 50-mesh sieve, placed in a 40 mL electronic nose sample bottle, and allowed to stand to allow the headspace bottle to be filled with sample gas. The electronic nose was used for detection at room temperature, wherein the cleaning time was 180 s, the air intake speed was 0.6 L / min, the detection time was 120 s, the injection volume was 10 mL, and the measurement was repeated 3 times.

[0022] More specifically, in order to collect the odor information of tangerine peel of different aging years, wherein the odor information includes aromatic compound information, nitrogen oxide information, sulfide information, terpenoid information, ester information, sterol information, triterpenoid information, aliphatic hydrocarbon oxygen-containing derivative information, amine information, hydrogen information, furan information, volatile organic compound information, ethylene information, lactone information and pyrazine information, the embodiment of the present invention collects the odor information through 14 sensors of the E-Nose type electronic nose, as shown in the following table.

[0023]

[0024] Among them, 1 to 14 represent the numbers of 14 sensors respectively. It should be noted that it can be noticed that different sensors in the table detect the same type of substances. For example, sensor 3 and sensor 12 both detect sulfides, but the specific substances detected are different. The reference substances detected by sensor 3 are thiols and thioethers, and the reference substance detected by sensor 12 is hydrogen sulfide.

[0025] In actual application, the average response value (14 sensors) of three measurements of each batch of samples was selected as the characteristic value.

[0026] Step S02, tangerine peels of different aging years are tested by HS-GC-MS under preset conditions to obtain total ion current graphs, and the relative percentage content of each component is calculated based on the total ion current graphs.

[0027] Specifically, 0.5 g of tangerine peel sample powder from different aging years was accurately weighed, the tangerine peel sample powder was sieved through a 50-mesh sieve, placed in a 20 mL headspace bottle, sealed with an aluminum cap, and measured in parallel three times, wherein the bottle was placed in a sample tray after sealing, the sample bottle heating temperature was 110°C, the quantitative loop temperature was 120°C, the transmission line temperature was 130°C, and the sample bottle equilibration time was 10 min.

[0028] It should be noted that the HS-GC-MS detection data were imported into Data Analysis 2013 software, and the relative percentage content of each component was calculated from each total ion current map after processing and using the area normalization method.

[0029] Step S03, integrating the relative percentage content of each component, qualitatively analyzing the integration result according to the mass spectrum of each peak through the mass spectrum of the standard database, and screening out volatile components with a matching degree greater than a preset value.

[0030] In this embodiment, after integration, the mass spectra of each peak are qualitatively analyzed by mass spectrometry of the National Institute of Standards and Technology (NIST) 20.L standard database built into the application software, and a search report is exported. Volatile components with a matching degree of ≥80% are screened out by searching by CAS number.

[0031] In addition, it is also possible to combine online databases and references, match the retention time, accurate molecular weight, fragment ions and compounds, align the retention time of the obtained data report, and perform multivariate statistical analysis on the processed data. For example, the fingerprint spectrum and radar map are drawn by Origin 2018 software; the heat map is drawn by TBtools.

[0032] Step S04, taking the volatile components as dependent variables and different years as independent variables, performing unsupervised PCA analysis and OPLS-DA analysis to screen the differential volatile components of tangerine peels of different aging years.

[0033] Specifically, unsupervised PCA analysis is principal component analysis, and OPLS-DA analysis is orthogonal partial least squares-discriminant analysis. SIMCA 14.1 software was used for OPLS-DA analysis, and SPSS 21.0 one-way ANOVA P < 0.05 and VIP (Variable Importance in the Projection) value > 1 were used to screen the differential volatile components of tangerine peel in different aging years.

[0034] Step S05, determining whether the differentiated volatile components are consistent with the odor information, if so, executing step S06.

[0035] In step S06, cluster analysis is performed on the differentiated volatile components, and it is determined whether the result of the cluster analysis is consistent with the results of the unsupervised PCA analysis and the OPLS-DA analysis. If so, step S07 is executed.

[0036] In step S07, the aroma activity value of each differentiated volatile component is calculated, and the target component in the differentiated volatile components is determined according to the aroma activity value.

[0037] It should be noted that the calculation formula for the aroma activity value is: OAV = concentration of aroma substance in the matrix / detection threshold of the substance in the matrix; Wherein, OAV represents the aroma activity value. In this embodiment, when OAV>1, it is determined that the volatile component plays a modifying role in the aroma of tangerine peel red. When OAV>10, it is determined that the volatile component is the key component of the overall aroma of tangerine peel, that is, the target component.

[0038] Step S08, establishing a discrimination model according to different aging years and the content of the target component that changes with the different aging years.

[0039] It can be understood that since the target component has been determined, the relationship between the year and the content of the target component can be determined by different aging years and the content of the target component that changes with different aging years, and the fitting curve between them can be determined by fitting.

[0040] Step S09, obtaining the content of the target component of the dried tangerine peel and inputting it into the discrimination model to obtain the aging year of the dried tangerine peel.

[0041] In summary, the method for identifying the aging year of tangerine peel in the above-mentioned embodiment of the present invention detects the volatile components in tangerine peel of different aging years by combining an electronic nose with HS-GC-MS technology, and performs data processing and analysis in combination with principal component analysis (PCA), orthogonal partial least squares method-discriminant analysis (OPLS-DA), cluster analysis and aroma activity value (OAV), screens out the differential components and key aroma components in the aging process of tangerine peel, explores the differences between different aging years, and finally determines the target components, and then establishes a discriminant model according to different aging years and the content of the target components that change with different aging years; obtains the content of the target components of tangerine peel, and inputs the discriminant model to obtain the aging year of tangerine peel, thereby realizing the non-destructive, rapid and accurate identification of the aging year of tangerine peel.

[0042] In order to verify the method for identifying the aging year of tangerine peel proposed in the embodiment of the present invention, specifically, 7 batches of tangerine peel harvested from 2017 to 2023 were selected. Calculated in natural years, the aging time was the current year (aging time was less than 1 year), 1 year, 2 years, 3 years, 4 years, 5 years and 6 years, respectively.

[0043] The electronic nose is used to detect and analyze the sensor data of tangerine peels of different aging years collected by the electronic nose to establish a radar map of odor information, such as Figure 2The figure shows the radar chart of the electronic nose of tangerine peel samples of different aging years, where the response value at the center of the radar chart is 0.00, and the response values ​​of each circle spreading outward from the center are 0.02, 0.04, 0.06, 0.08, 0.10, 0.12, and 0.14, respectively. The 14 sensors of the electronic nose have certain similarities in the volatile components of tangerine peel aged from the current year to the sixth year, but the response values ​​are different, with greater contributions on sensor 1, sensor 2, sensor 5, sensor 8, sensor 9, and sensor 11. Comparing the response values ​​of tangerine peel of different aging years on the above six sensors, it is found that the response intensity of tangerine peel to sensor 2, sensor 5, sensor 11, and sensor 9 gradually decreases with the increase of years. There are significant differences in sensor S1 (p=0.00) and sensor S8 (p=0.007). Based on this, it can be inferred that the content of nitrogen oxides / low molecular amines, terpenes / esters, and volatile organic compounds in tangerine peel is relatively high, and the aroma components of tangerine peel in different aging years are similar, mainly reflected in the difference in content. Among them, the response values ​​of sensor 1 and sensor 8 in 2018 showed significant differences, and the difference in results caused by the source and environment cannot be ruled out.

[0044] Furthermore, in order to study the characteristic components of tangerine peel in different aging years, the HS-GC-MS technology was used to analyze and identify the volatile components and relative contents of tangerine peel from 2017 to 2023. A total of 113 volatile components were identified, including 55 olefin compounds, 23 alcohol compounds, 14 aldehyde compounds, 4 phenol compounds, 4 ketone compounds, 6 ester compounds, 3 alkane compounds, 1 ether compound and 3 undetermined compounds.

[0045] The overall volatile component content in tangerine peel aged from 2017 to 2023 shows a downward trend with the increase of aging years, and the relative content of each component also changes. Among them, D-limonene has the highest content, accounting for 54.29%-72.98% of the total. It is a component with special fragrance and pungent odor, which can be used to prepare flavors and fragrances; other volatile components with relatively high content are linalool (0.52%-6.97%), germacrene D (5.51%-0.27%), γ-terpinene (3.22%-6.07%), and levorotatory-α-pinene (1.04%-4.43%). The relative content of levorotatory-α-pinene, D-limonene, and γ-terpinene components increases with the increase of aging years, while the relative content of germacrene D and linalool gradually decreases with the increase of aging years. Please refer to Figure 3 , is the relative content chart of volatile components of tangerine peel aged from 2017 to 2023. It can be found that the relative content of olefin components in tangerine peel from the first year to 6 years of aging mainly increases with the years, while the relative content of alcohols decreases with the years. The main volatile components in tangerine peel are olefins and alcohols.

[0046] From a qualitative point of view, the types of volatile components in each year are relatively small, with only a few differences. Comparing the peak areas of each year, the peak areas of the same volatile substances in tangerine peels of different years show an up-and-down trend, but most of the volatile substances are still mainly showing a downward trend. The reason may be related to factors such as climate and environment during the growth of samples of each year, or factors such as temperature, humidity, and microbial environment during storage. Even different batches of medicinal materials of the same year will have different degrees of differences.

[0047] Furthermore, an unsupervised PCA analysis was performed using 169 volatile components with a matching degree greater than 80% in the preliminary screening of the NIST20.0 retrieval report as dependent variables and different years as independent variables. The fitting index R2X was 0.809 and Q2 was 0.636, indicating that the model was stable and reliable. Figure 4 , is an unsupervised PCA analysis chart. The results show that there are significant differences in the volatile components of tangerine peels of different aging years. Tangerine peels of different aging years can be divided into two categories. In order to further explore the differential volatile components between samples of different years, OPLS-DA analysis can be used to effectively distinguish tangerine peel samples of different years. Please refer to Figure 5 , which is the OPLS-DA analysis chart. The independent variable fitting index (R2x) in OPLS-DA is 0.980, the dependent variable fitting index (R2y) is 0.983, and the model prediction index (Q2) is 0.956. R2 and Q2 are more than 0.5, which means that the model fitting results are acceptable. The OPLS-DA model was subjected to 200 permutation tests, and the intersection point of the Q2 regression line and the vertical axis was less than 0, indicating that the model was not overfitted and the model verification was effective. It is believed that the results can be used for the identification and analysis of tangerine peel of different aging years, which further verifies that the volatile components of tangerine peel of different aging years are significantly different.

[0048] The fingerprints of volatile components of different aging years are established based on the peak retention time, peak area value and other related parameters of these volatile components. Figure 6 , which are the fingerprints of volatile components of different aging years. There are obvious differences between the fingerprints of volatile components of tangerine peel aged from 1 year to 6 years, which once again verifies the reliability of the above results. The types of volatile components of samples of different aging years are similar, mainly reflected in the differences in the total content of various substances.

[0049] It should be noted that due to the differences in volatile components between tangerine peels of different aging years, in order to reduce the interference of irrelevant variables within the group on the results, the OPLS-DA model was used to analyze the volatile components of tangerine peels of different aging years, with VIP value>1 and P<0.05 as the standard, please refer to Figure 7, which is the OPLS-DA model VIP diagram, screens the volatile components related to the differences in tangerine peels of different aging years. A total of 25 differential compounds were screened, including 15 olefins, 6 alcohols, 1 aldehyde, and 1 ester. Olefins and alcohols are the main compound categories of the differential components of tangerine peels of different aging years, which is consistent with the results of the electronic nose data. Among them, the common differential components in the samples aged from the first year to the sixth year are 21 compounds, including L-α-pinene, L-β-pinene, myrcene, p-cymene, D-limonene, γ-terpinene, linalool, α-terpineol, decanal, D-citronellol, and thymol methyl ether. A cluster analysis was performed on the differential components, and the results showed that the tangerine peel aged from the current year to 6 years was divided into two categories: 2022, 2017, and 2018 were Class I, and 2019, 2021, 2023, and 2020 were Class II, which was consistent with the results of the above multivariate statistical analysis.

[0050] Finally, an OAV analysis of the aroma of tangerine peels of different aging years was conducted. It should be noted that the content of volatile components cannot be used as the only indicator to determine the aroma characteristics of the sample. Usually, aroma components with higher aroma activity values ​​(OdorActivity Value, OAV) are used as characteristic aroma substances. The concentration and threshold of a single component determine its contribution to the overall aroma of the sample.

[0051] The OAV of individual volatile components was calculated to evaluate their contribution to the overall aroma of dried tangerine peel. A total of 18 aroma components were available for calculating OAV, among which myrcene (0.72-1.37), D-limonene (1.45-2.15), linalool (2.36-34.55), decanal (1.10-9.30), D-citronellol (5.75-25.00), thymol methyl ether (5.38-10.00), germacrene B (0.19-1.87), and carveol (840-1360) had OAV values ​​greater than 1. It is believed that these differential aroma substances may play an important role in discriminating the aroma characteristics of dried tangerine peel aged from one year to six years. Among them, the OAVs of linalool in tangerine peel aged from the first year to 5 years, D-citronellol in tangerine peel aged from the first year to 3 years, and carveol in tangerine peel aged from 4 years to 5 years are all higher than 10, and it is believed that these volatile substances may be the key aroma components in tangerine peel. Among them, alcohols, aldehydes, and olefins have a greater impact on the volatile organic compounds of the aging year. The main flavor substances in tangerine peel are still alcohols, aldehydes, terpenes, etc. In summary, the OAVs of linalool, D-citronellol, and carveol are all higher than 10, which may be the key aroma components in tangerine peel, that is, linalool, D-citronellol, and carveol are determined as target components.

[0052] In this embodiment, a discrimination model is established according to different aging years and the contents of linalool, D-citronellol and carveol that vary with different aging years; the contents of linalool, D-citronellol and carveol in tangerine peel are obtained and input into the discrimination model to obtain the aging year of tangerine peel.

[0053] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0054] The above embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention patent shall be subject to the attached claims.

Claims

1. A method for identifying the aging year of tangerine peel, characterized in that: The method comprises: The tangerine peels of different aging years are detected by an electronic nose at room temperature to obtain the odor information of the tangerine peels of different aging years, and the odor information is used to provide direction for subsequent HS-GC-MS analysis; The dried tangerine peels of different aging years were tested by HS-GC-MS under preset conditions to obtain total ion current graphs, and the relative percentage content of each component was calculated based on the total ion current graphs; The relative percentage content of each component is integrated, and the integration results are qualitatively analyzed by mass spectrometry of the standard database according to the mass spectrum of each peak, and the volatile components with a matching degree greater than a preset value are screened out; The volatile components were used as dependent variables and different years were used as independent variables to conduct unsupervised PCA analysis and OPLS-DA analysis to screen the differential volatile components of tangerine peels from different aging years; determining whether the differentiated volatile components are consistent with the odor information; If it is determined that the differentiated volatile components are consistent with the odor information, cluster analysis is performed on the differentiated volatile components, and it is determined whether the results of the cluster analysis are consistent with the results of the unsupervised PCA analysis and the OPLS-DA analysis; If the results of the cluster analysis are judged to be consistent with the results of the unsupervised PCA analysis and the OPLS-DA analysis, the aroma activity value of each differentiated volatile component is calculated, and the target component among the differentiated volatile components is determined based on the aroma activity value; According to different aging years and the content of target components that change with different aging years, a discriminant model is established; The content of the target component of the dried tangerine peel is obtained and input into the discrimination model to obtain the aging year of the dried tangerine peel.

2. The method for identifying the aging year of tangerine peel according to claim 1, wherein: In the step of detecting tangerine peel of different aging years by using an electronic nose at room temperature, 0.5 g of tangerine peel sample powder of different aging years is weighed respectively, the tangerine peel sample powder is sieved through a 50-mesh sieve, placed in a 40 mL electronic nose sample bottle, left to stand so that the headspace bottle is filled with sample gas, and detected by using an electronic nose at room temperature, wherein the cleaning time is 180 s, the air intake speed is 0.6 L / min, the detection time is 120 s, the injection volume is 10 mL, and the parallel determination is repeated 3 times.

3. The method for identifying the aging year of tangerine peel according to claim 2, wherein: The odor information includes aromatic compound information, nitrogen oxide information, sulfide information, terpenoid information, ester information, sterol information, triterpenoid information, aliphatic hydrocarbon oxygen-containing derivative information, amine information, hydrogen information, furan information, volatile organic compound information, ethylene information, lactone information and pyrazine information.

4. The method for identifying the aging year of tangerine peel according to claim 1, wherein: In the step of detecting tangerine peel of different aging years by HS-GC-MS under preset conditions, 0.5 g of tangerine peel sample powder of different aging years is weighed respectively, the tangerine peel sample powder is sieved through a 50-mesh sieve, placed in a 20 mL headspace bottle, sealed with an aluminum cap, and measured in parallel 3 times, wherein the bottle is placed in a sample tray after sealing, the sample bottle is heated at 110° C., the quantitative loop temperature is 120° C., the transmission line temperature is 130° C., and the sample bottle equilibration time is 10 min.

5. The method for identifying the aging year of tangerine peel according to claim 1, wherein: The preset value is 80%.

6. The method for identifying the aging year of tangerine peel according to claim 1, wherein: In the step of calculating the aroma activity value of each differentiated volatile component, the calculation formula of the aroma activity value is: OAV = concentration of aroma substance in the matrix / detection threshold of the substance in the matrix; Among them, OAV stands for aroma activity value.

7. The method for identifying the aging year of tangerine peel according to claim 6, characterized in that: In the step of determining the target component in the differentiated volatile components according to the aroma activity value, when OAV>1, it is determined that the volatile component plays a modifying role in the aroma of tangerine peel red, and when OAV>10, it is determined that the volatile component is the key component of the overall aroma of tangerine peel, that is, the target component.

8. The method for identifying the aging year of tangerine peel according to claim 1, wherein: In the step of taking the volatile components as the dependent variable and different years as the independent variables, performing unsupervised PCA analysis and OPLS-DA analysis to screen the differentiated volatile components of tangerine peel in different aging years, SIMCA 14.1 software was used for OPLS-DA analysis, and SPSS21.0 one-way analysis of variance P<0.05 and VIP value>1 were used to screen the differentiated volatile components of tangerine peel in different aging years.

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