CN112782114A - Method for identifying aging years of dried orange peel - Google Patents
Method for identifying aging years of dried orange peel Download PDFInfo
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- CN112782114A CN112782114A CN202011562173.4A CN202011562173A CN112782114A CN 112782114 A CN112782114 A CN 112782114A CN 202011562173 A CN202011562173 A CN 202011562173A CN 112782114 A CN112782114 A CN 112782114A
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- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
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- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
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Abstract
The invention relates to a method for identifying the aging years of dried orange peel, which comprises the following steps: constructing an identification function model by using the independent variable X and the dependent variable Y; taking pericarpium Citri Tangerinae to be tested, detecting the relative content of volatile oil components positively correlated with aging year value and the relative content of volatile oil components negatively correlated with aging year value, and inputting into the discrimination function model. According to the invention, the dried orange peel to be detected is cut into blocks and then detected, so that the volatilization loss of part of volatile oil components caused by heat generated in the powdering process is avoided, and the obtained volatile oil data is close to the true value as much as possible. The invention adopts an advanced headspace-solid phase microextraction method to extract volatile components of a dried orange peel analysis sample, and can avoid the dried orange peel sample from oxidation, degradation or biochemical reaction and the like compared with the traditional heating reflux method. The method can be accurately used for identifying the citrus reticulata blanco with the aging year of more than 5 years, particularly 5 to 33 years, and the identification error of the citrus reticulata blanco with the aging year of the citrus reticulata blanco can not occur due to the large aging year and the small change of the contained volatile oil of the citrus reticulata blanco.
Description
Technical Field
The invention relates to the technical field of traditional Chinese medicine identification, in particular to a method for identifying the aging years of dried orange peel.
Background
The pottery hong Jing of the Nansong Liang Dynasty firstly proposes ' good for a long time ' in famous medical records '. The tangerine peel is defined as the tangerine peel of the tea branch with the storage time of three years or more in a natural aging environment in the local standard DB 44/T604-2009 geographical designation product Xinhui tangerine peel in Guangdong province. In the current market of the dried orange peels, the pursuit for the dried orange peels in the high years is not reduced all the time, and the price of the dried orange peels rises by 15-20% every year due to the mildewing, worm damage and loss caused by the change of the sun-drying or aging environment in the first 3-5 years. The price of new peel in a new producing area is about 150 yuan/jin, the price of dried orange peel after aging for 5 years is about 450 yuan/jin, the price of dried orange peel after aging for 25 years is about 8,000 yuan/jin, and the price of dried orange peel after aging for 50 years can be as high as about 380,000 yuan/jin, thereby generating the saying that one or two dried orange peels are one or two jin, and one hundred years dried orange peel is superior to gold. The age of aging has a decisive influence on the price of the dried orange peel, so that the marketable merchants earn high profits for old and new peel camouflage as old dried orange peels, thereby causing market disorder of 'false age'. Therefore, the method for accurately and quickly identifying the dried orange peels in years is particularly important in the market industry of the dried orange peels.
Regarding naturally aged pericarpium citri reticulatae, human olfaction discovers that the flavor of the Xinhui pericarpium citri reticulatae in different years with large span, such as 3 years, 10 years, 20 years, 30 years and the like, has difference, and related documents report about the research on the relation between the volatile components of the pericarpium citri reticulatae and the aging years. For example, the patent of ' analysis of components of pericarpium citri reticulatae volatile oil with different storage times ' is published in the severe cold state ', the document considers that the total amount of the volatile oil is reduced along with the increase of the aging time, but the change trend of the components of the volatile oil and the internal rules between years are not clarified. Similarly, chuanxiongol et al published "solid phase microextraction optimization/GC-MS method for analyzing volatile components of citrus peel in different years", which used headspace solid phase microextraction (HS-SPME) in combination with gas chromatography mass spectrometry (GC-MS) to analyze citrus peel in different years, but which is limited only to the determination of volatile oil components and does not disclose the existence of rules between volatile oil and year. For another example, an infrared spectroscopy (FTIR) method for rapidly identifying the years of the dried orange peel and the pericarpium citri reticulatae mainly comprises the following steps: s1, collecting pericarpium Citri Tangerinae and pericarpium Citri Reticulatae Chachiensis medicinal materials of different producing areas and different years as samples, collecting infrared spectra of the collected samples to obtain infrared spectrogram corresponding to each sample, and establishing infrared spectral database of pericarpium Citri Tangerinae and pericarpium Citri Reticulatae Chachiensis medicinal materials; s2, observing an infrared spectrum profile chart by analyzing the established infrared spectrum database, comparing the differences of the dried orange peels or the pericarpium citri reticulatae in different producing areas and years, and determining a characteristic absorption peak and a base peak for year comparison and judgment; s3, collecting the infrared spectrum of the dried orange peel or the pericarpium citri reticulatae, comparing the obtained infrared spectrum with the spectrogram in the spectral library, and carrying out qualitative judgment of the year. The technology can judge the dried orange peel with the aging year more than 5 years according to the absorption condition of a specific wave band, but the method cannot judge the specific aging year of the dried orange peel. For example, the document uses a GC-MS method to analyze 11 volatile oil components of dried orange peels of different storage years within 30 years, and the result shows that the content of other main volatile oil components does not show a descending trend along with the increase of the storage years except for 2-methylamino-methyl benzoate, and the document uses the content ratio of beta-myrcene to 2-methylamino-methyl benzoate peaks and the aging years to construct a logarithmic function, wherein the coefficient is 0.86, and the dried orange peels are difficult to accurately identify.
The dried orange peel with the moisture content, sugar content and volatile oil content of three years or more is reported to be less, the dried orange peel is not easy to burn, get damp, mildew and moth-eaten, and the characteristics of the newly-loved dried orange peel aged for more than 5 years tend to be in a stable state and are not easy to be influenced by the surrounding environment. Therefore, the volatile components gradually change in a less pronounced manner with the increase in aging years. Under the circumstance, how to utilize volatile components to realize accurate identification of the years of the dried orange peels becomes a technical problem in the field.
Disclosure of Invention
Based on the above, the main purpose of the invention is to provide a method for identifying the aging years of the dried orange peel. The method can be accurately used for identifying the citrus reticulata blanco with the aging year of more than 5 years, particularly 5 to 33 years, and the identification error of the citrus reticulata blanco with the aging year of the citrus reticulata blanco can not occur due to the large aging year and the small change of the contained volatile oil of the citrus reticulata blanco.
The purpose of the invention is mainly realized by the following technical scheme:
a method for identifying the age of citrus peel, said method comprising:
constructing an identification function model by using X and Y; wherein the content of the first and second substances,
the X is an aging year value;
y is the ratio of the content A to the content B;
the content A is the sum of the contents of the volatile oil components which are positively correlated with the aging year value,
the content B is the sum of the contents of the volatile oil components which are in negative correlation with the aging year value;
the volatile oil components positively correlated with the aging year value comprise beta-myrcene, dextro-limonene, gamma-terpinene and terpinolene, or comprise beta-myrcene, dextro-limonene, gamma-terpinolene, terpinolene and auraldehyde;
the volatile oil component which is negatively correlated with the aging year value comprises L-carveol and 2,6,11, 15-tetramethyl-hexadecane-2, 6,8,10, 14-pentaene;
and taking the pericarpium citri reticulatae to be detected, detecting the content of the volatile oil component positively correlated with the aging year value and the content of the volatile oil component negatively correlated with the aging year value, and inputting the contents into the function model.
In one embodiment, the equation type of the function model is a complex equation, a growth equation, an exponential equation, or a logistic equation.
In one embodiment, the composite equation is: y613.555 × 0.893XR ═ 0.974; or/and the growth equation is: y ═ e6.419-0.113XR ═ 0.974; or/and the exponential equation is: y613.555 × e-0.113XR ═ 0.974; or/and the logistic equation is as follows: y1/(1/. mu. + 0.002X 1.12)X) μ is the upper limit of the function model, and R is 0.974.
In one embodiment, the aging mode of the dried orange peel is natural aging.
In one embodiment, the dried orange peel is pericarpium citri reticulatae.
In one embodiment, the age of the citrus peel is greater than 5 years.
In one embodiment, the aging period of the dried orange peel is 5 years to 33 years.
In one embodiment, the detecting comprises:
and extracting volatile oil components positively correlated with the aging year value and volatile oil components negatively correlated with the aging year value in the pericarpium citri reticulatae to be detected by headspace-solid phase microextraction, and analyzing the volatile oil components positively correlated with the aging year value and the volatile oil components negatively correlated with the aging year value by gas chromatography-mass spectrometry.
In one embodiment, the headspace-solid phase microextraction is carried out at an extraction temperature of 85 ℃ to 95 ℃.
In one embodiment, the dried orange peel to be tested is pretreated as follows: taking pericarpium Citri Tangerinae to be detected, and cutting into pieces.
In one embodiment, the condition setting of the gas chromatograph comprises: adopting a temperature programming mode, keeping the initial temperature of the column at 45-55 ℃ for 1.8-2.2 min; raising the temperature to 68-72 ℃ at the speed of 2.8-3.2 ℃/min, and keeping the temperature for 8-12 min; raising the temperature to 108-112 ℃ at the speed of 7.8-8.2 ℃/min, and keeping the temperature for 4.5-5.5 min; raising the temperature to 208-212 ℃ at the speed of 3.8-4.2 ℃/min, and keeping the temperature for 1.8-2.2 min.
In one embodiment, the condition setting of the gas chromatograph further comprises:
a chromatographic column: HP-5MS (30 mm. times.0.25 μm);
carrier gas: he;
flow rate: 0.8mL/min to 1.2 mL/min;
sample inlet temperature: 220 to 240 ℃;
the split ratio is as follows: (28-32): 1.
In one embodiment, the condition setting of the mass spectrum comprises:
ion source temperature: 225-235 ℃;
electron energy: 68eV to 72 eV;
ion collection range: 35m/z to 450 m/z.
The beneficial effects of the invention include:
the method takes the ratio of the sum of the relative contents of the volatile oil components which are in positive correlation with the aging year value and the sum of the relative contents of the volatile oil components which are in negative correlation with the aging year value of a proper type as dependent variables, takes the aging year value as an independent variable, constructs a function model for identifying the years of the dried orange peel, and then brings the volatile oil components detected from the dried orange peel to be detected into the function model so as to determine the aging years of the dried orange peel. The method can be accurately used for identifying the citrus reticulata blanco with the aging year of more than 5 years, particularly 5 to 33 years, and the identification error of the citrus reticulata blanco with the aging year of the citrus reticulata blanco can not occur due to the large aging year and the small change of the contained volatile oil of the citrus reticulata blanco.
Drawings
FIG. 1 is a total ion flow diagram (TIC) of the extraction temperature of 90 ℃ and 45 ℃ in a temperature increasing program (I);
FIG. 2 is a temperature program (temp.) Total ion flow graph (TIC);
FIG. 3 is a temperature program (Total ion flow diagram (TIC));
FIG. 4 is a total ion flow chart (TIC) of a temperature program (R);
FIG. 5 is a temperature program (Total ion flow graph (TIC));
FIG. 6 is a graph showing the total ion flow (TIC) of dried orange peel samples aged for 6 years in a Mandarin orange garden base of Jiangmen;
FIG. 7 is a graph showing the total ion flow (TIC) of a dried orange peel sample aged 11 years in a Mandarin orange garden base of Jiangmen;
FIG. 8 is a total ion flow graph (TIC) of dried orange peel samples aged 12 years in a Mandarin orange garden base of Jiangmen;
FIG. 9 is a graph showing the total ion flow (TIC) of dried orange peel samples aged for 14 years in bases filled with citrus from Jiangmen;
FIG. 10 is a total ion flow graph (TIC) of dried orange peel samples aged for 20 years in a Mandarin orange garden base of Jiangmen;
FIG. 11 is a graph showing the total ion flow (TIC) of a dried orange peel sample aged for 33 years in a Mandarin orange garden base of Jiangmen;
FIG. 12 is a total ion flow graph (TIC) of dried orange peel samples aged 6 years in Jiangmen high-quality base;
FIG. 13 is a total ion flow graph (TIC) of a 9-year aged pericarpium Citri Tangerinae sample in Jiangmen high-quality base;
FIG. 14 is a total ion flow chart (TIC) of dried orange peel samples aged 12 years in Jiangmen high-quality bases;
FIG. 15 is a total ion flow graph (TIC) of a 24-year aged pericarpium Citri Tangerinae sample in Jiangmen high-quality base;
FIG. 16 is a graph of an authentication model constructed in accordance with the present invention;
FIG. 17 is a flow chart of the present invention.
Detailed Description
In order that the invention may be more fully understood, reference will now be made to the following description. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
A method for identifying the age of citrus peel, said method comprising:
constructing an identification function model by using X and Y; wherein the content of the first and second substances,
the X is an aging year value;
the Y is the ratio of the content A to the content B,
the content A is the sum of the contents of the volatile oil components which are positively correlated with the aging year value,
the content B is the sum of the contents of the volatile oil components which are in negative correlation with the aging year value;
the volatile oil components positively correlated with the aging year value comprise beta-myrcene, dextro-limonene, gamma-terpinene and terpinolene, or comprise beta-myrcene, dextro-limonene, gamma-terpinolene, terpinolene and auraldehyde;
the volatile oil component which is negatively correlated with the aging year value comprises L-carveol and 2,6,11, 15-tetramethyl-hexadecane-2, 6,8,10, 14-pentaene;
and taking the pericarpium citri reticulatae to be detected, detecting the content of the volatile oil component positively correlated with the aging year value and the content of the volatile oil component negatively correlated with the aging year value, and inputting the contents into the function model.
The content in the embodiment of the present invention refers to a relative content, which refers to a content of a certain component relative to all components of the sample itself.
Preferably, the equation type of the function model is a complex equation, a growth equation, an exponential equation or a logistic equation.
Preferably, the composite equation is: y613.555 × 0.893X，R＝0.974。
Preferably, the growth equation is: y ═ e6.419-0.113X，R＝0.974。
Preferably, the exponential equation is: y613.555 × e-0.113X，R＝0.974。
Preferably, the logistic equation is: y1/(1/. mu. + 0.002X 1.12)X) μ is the upper limit of the function model, and R is 0.974.
Preferably, the aging mode of the dried orange peel is natural aging. The method provided by the embodiment of the invention can be suitable for identifying the aging years of the naturally aged pericarpium citri reticulatae, and can be understood that whether the pericarpium citri reticulatae to be detected is the naturally aged pericarpium citri reticulatae needs to be judged before the aging years of the naturally aged pericarpium citri reticulatae are identified, and the method provided by the embodiment of the invention is not particularly limited to the judging mode, including but not limited to the method disclosed in CN 111983061A.
Preferably, the dried orange peel is pericarpium citri reticulatae. The citrus peel of the invention includes but is not limited to citrus peel of the Xinhui province.
Preferably, the aging period of the dried orange peel is more than 5 years.
Preferably, the aging period of the dried orange peel is 5 to 33 years.
Preferably, the detecting comprises:
and extracting volatile oil components positively correlated with the aging year value and volatile oil components negatively correlated with the aging year value in the pericarpium citri reticulatae to be detected by headspace-solid phase microextraction, and analyzing the volatile oil components positively correlated with the aging year value and the volatile oil components negatively correlated with the aging year value by gas chromatography-mass spectrometry.
Compared with the traditional heating reflux method, the extraction method provided by the embodiment of the invention can avoid oxidation, degradation or biochemical reaction and the like of the dried orange peel sample, and can accurately reflect the content change of each component of volatile oil in the dried orange peel in different years, so that the extracted volatile oil can be close to the true value of the dried orange peel.
Preferably, the extraction temperature adopted by the headspace-solid phase microextraction is 85-95 ℃, for example, 90 ℃ can be adopted, and the extraction temperature is preferably adopted in the embodiment of the invention, so that more volatile components can be extracted. It is understood that the extraction time can be adjusted within the preferred extraction temperature range of the embodiment of the present invention, for example, 35min to 45 min. Likewise, other extraction conditions may be moderately optimized.
Preferably, the dried orange peel to be detected is pretreated as follows: taking the dried orange peel to be detected, and cutting into blocks. In the embodiment of the invention, when the volatile components of the dried orange peel are extracted by headspace-solid phase microextraction, the dried orange peel is preferably cut into pieces, such as small blocks with the side length of 1cm, instead of crushing the dried orange peel into powder.
Preferably, the condition setting of the gas chromatography comprises: adopting a temperature programming mode, keeping the initial temperature of the column at 45-55 ℃ for 1.8-2.2 min; raising the temperature to 68-72 ℃ at the speed of 2.8-3.2 ℃/min, and keeping the temperature for 8-12 min; raising the temperature to 108-112 ℃ at the speed of 7.8-8.2 ℃/min, and keeping the temperature for 4.5-5.5 min; raising the temperature to 208-212 ℃ at the speed of 3.8-4.2 ℃/min, and keeping the temperature for 1.8-2.2 min.
Preferably, the condition setting of the gas chromatography further comprises:
a chromatographic column: HP-5MS (30 mm. times.0.25 μm);
carrier gas: he;
flow rate: 0.8mL/min to 1.2 mL/min;
sample inlet temperature: 220 to 240 ℃;
the split ratio is as follows: (28-32): 1.
Further preferably, the setting of the conditions of the gas chromatograph comprises:
adopting Agilent HP-5MS (30mm multiplied by 0.25 mu m) chromatographic column, taking high-purity He as carrier gas, setting the flow rate at 1.0mL/min, setting the injection port temperature at 230 ℃, adopting a temperature programming mode, setting the initial temperature of the column at 50 ℃, and keeping for 2 min; raising the temperature to 70 ℃ at the speed of 3 ℃/min, and keeping the temperature for 10 min; raising the temperature to 110 ℃ at the speed of 8 ℃/min, and keeping the temperature for 5 min; the temperature was raised to 210 ℃ at a rate of 4 ℃/min and held for 2 min. The split ratio was 30: 1.
Preferably, the condition setting of the mass spectrum comprises:
ion source temperature: 225-235 ℃;
electron energy: 68 m/z-72 eV;
ion collection range: 35m/z to 450 m/z.
Further preferably, the condition setting of the mass spectrum comprises:
mass Spectrometry (MS) conditions: the ion source temperature is 230 ℃, the electron energy is 70eV, and the ion collection range is 35-450 m/z.
For convenience of understanding, the present invention provides the following embodiments, wherein the embodiments of the present invention select the dried orange peels with the aging year of 5-33 years, including 6 years, 11 years, 12 years, 14 years, 20 years and 33 years, and establish an identification model of the aged years of the dried orange peels based on the dynamic change rule of the volatile oil components in the dried orange peels of different years (see fig. 17 in the process), and the coefficient of the identification model is as high as 0.974. The identification model truly and objectively reflects the difference between the volatile oil components of the dried orange peels in different years (namely the difference of the odors of the dried orange peels in different years), and can avoid the influence of factors such as the production place, the harvesting period, the drying mode, the storage condition, the processing method and the like on the natural aged dried orange peel volatile oil, thereby accurately identifying the aged dried orange peels between 5 and 33 years.
Example 1
1 sample information
1.1 analysis of samples
TABLE 1. New Hui Tangerine Peel analysis sample information for different years
1.2 validation samples
TABLE 2 sample information for verification of pericarpium Citri Reticulatae in Xinhui of different years
2 apparatus
7890B-5977A gas chromatography-mass spectrometer (Agilent, USA); 75 μm PDMS/DVB solid phase microextraction instrument-fiber head (SUPELCO, Inc., USA, Gray), 25mL SPME special sampling bottle; model BS110S electronic analytical balance (sydoris, germany); WXJ type pulverizer (Shanghai Kaixuan Chinese medicine machinery manufacturing Co., Ltd.).
3 determination of the volatile oil component
3.1 sample pretreatment method
Cutting pericarpium Citri Tangerinae sample into small blocks with side length of 1cm, placing 1.0g in 250mL headspace bottle, sealing, balancing in 90 deg.C water bath for 10min, inserting solid phase extraction fiber 50/30 μm CAR/DVB/PDMS headspace extracting for 40min, desorbing at 250 deg.C for 3min, and injecting sample.
3.1.1 sample size optimization
Considering that the heat generated in the powdering process exceeds room temperature easily, so that part of volatile oil components may volatilize during the crushing process, when the volatile components of the dried orange peel are extracted by adopting HS-SPME, the influence of the cut sample (small square with the side length of 1 cm) and the crushed sample (passing through a No. 3 sieve) on the volatile oil components is compared.
The result shows that the number of the components of the sample is not different under the conditions of shearing and crushing, but the ratio of the components has certain difference, which indicates that the heat generated by the crushing process can influence the proportion of the volatile oil components of the sample; it has further been shown that using the pulverized powder as a research sample may distort the ratios between the measured volatile oil components, while the data obtained by shearing the sample may approach the true values. Therefore, the test chooses to treat the citrus peel samples in a shear-breaking manner.
3.1.2 selection of sample extraction temperature
The research in the prior literature (Chunzou, Chentong, Helisu, and the like. solid phase microextraction optimization/GC-MS analysis of volatile components of dried orange peel in different years [ J ]. modern food technology, 2017,33(7): 238-: the number of peaks generated by GC-MS is gradually increased along with the increase of the extraction temperature of the dried orange peel sample, when the extraction temperature reaches 90 ℃, the number of peaks is the largest, and when the temperature is continuously increased, the number of peaks is reduced; on the other hand, the present study compared the extraction temperatures of 90 ℃ and 45 ℃ and found that the number of peaks at 90 ℃ was more than 45 ℃ as shown in FIG. 1. Therefore, the study uses 90 ℃ as the extraction temperature of the citrus peel.
3.2 chromatographic conditions
Adopting Agilent HP-5MS (30mm multiplied by 0.25 mu m) chromatographic column, taking high-purity He as carrier gas, setting the flow rate at 1.0mL/min, setting the injection port temperature at 230 ℃, adopting a temperature programming mode, setting the initial temperature of the column at 50 ℃, and keeping for 2 min; raising the temperature to 70 ℃ at the speed of 3 ℃/min, and keeping the temperature for 10 min; raising the temperature to 110 ℃ at the speed of 8 ℃/min, and keeping the temperature for 5 min; the temperature was raised to 210 ℃ at a rate of 4 ℃/min and held for 2 min. The split ratio was 30: 1.
Mass Spectrometry (MS) conditions: the ion source temperature is 230 ℃, the electron energy is 70eV, and the ion collection range is 35-450 m/z.
3.2.1 temperature program optimization
The study compared the following five temperature program:
firstly, keeping the initial temperature of the column at 70 ℃ for 1 min; the temperature was raised to 210 ℃ at a rate of 4 ℃/min for 4min, see FIG. 1.
② keeping the initial temperature of the column at 50 ℃ for 2 min; raising the temperature to 70 ℃ at the speed of 3 ℃/min, and keeping the temperature for 5 min; raising the temperature to 100 ℃ at the speed of 6 ℃/min, and keeping the temperature for 5 min; raising the temperature to 210 ℃ at the speed of 4 ℃/min, and keeping the temperature for 4 min; the temperature was raised to 250 ℃ at a rate of 10 ℃/min for 2min, see FIG. 2.
③ keeping the initial temperature of the column at 50 ℃ for 2 min; raising the temperature to 70 ℃ at the speed of 3 ℃/min, and keeping the temperature for 10 min; raising the temperature to 100 ℃ at the speed of 3 ℃/min, and keeping the temperature for 5 min; the temperature was raised to 210 ℃ at a rate of 5 ℃/min for 4min, see FIG. 3.
Fourthly, keeping the initial temperature of the column at 50 ℃ for 2 min; raising the temperature to 70 ℃ at the speed of 3 ℃/min, and keeping the temperature for 10 min; raising the temperature to 100 ℃ at the speed of 3 ℃/min, and keeping the temperature for 5 min; the temperature was raised to 210 ℃ at a rate of 5 ℃/min for 4min, see FIG. 4.
Fifthly, keeping the initial temperature of the column at 50 ℃ for 2 min; raising the temperature to 70 ℃ at the speed of 3 ℃/min, and keeping the temperature for 10 min; raising the temperature to 110 ℃ at the speed of 8 ℃/min, and keeping the temperature for 5 min; the temperature was raised to 210 ℃ at a rate of 4 ℃/min for 2min, see figure 5.
As a result, it was found that the number of peaks obtained by the fifth temperature raising step was large, the separation effect was good, and the time was short. Therefore, the present study determined the fifth temperature-raising program as the optimum condition.
3.3 determination of
All analysis samples and verification samples are determined by the determined headspace-solid phase microextraction (HS-SPME) -GC-MS technology, and 2 groups of parallel experiments are set for each group of samples; the resulting mass spectral data were matched against the NIST14 database.
The chromatogram of the sample is shown in FIGS. 6-11; the chromatogram of the sample is shown in FIGS. 12-15.
4 matching and normalizing volatile oil components
4.1 identification of volatile oil Components
In the research, GC-MS is adopted to measure the volatile oil components and the relative percentage content of dried orange peels in 6 different aging years from M _6 to M _33 years in a Mandarin orange garden, after the obtained mass spectrum data is matched with a NIST14 database, each group of data is collated, high matching components (qualitative matching degree >80) of each peak are selected, 75 volatile oil components are matched, and the specific results are shown in a table 3.
TABLE 3 relative content of essential oil component of orange peel in 6 different aging years (n ═ 2) in Manyu garden
Note: nd, undetected or qualitatively matching < 80
4.2 consensus Components
As can be seen from Table 3, the total volatile components contained in the dried orange peels of 6 different aging years are 23 and are numbered from S1 to S23, and the specific information is shown in Table 4. As can be seen from Table 4, the relative contents of the common components in the citrus reticulata blanco are obviously different in different aging years, and show various changes such as rising, falling or rising first and then falling in different aging years.
TABLE 4. essential oil common component and relative content for different aging years (n 2)
5 analysis of change rule of volatile oil components along with aging years
5.1 correlation analysis
To explore the correlation between the consensus and the age, Pearson correlation analysis was performed using SPSS19.0 software, and the results are shown in table 5.
TABLE 5.23 correlation analysis between consensus and year
| Common components | Correlation coefficient with year | Significance (Sig. double-sided) |
| S1 | -0.55 | 0.258 |
| S2 | -0.448 | 0.373 |
| S3 | -0.549 | 0.259 |
| S4 | -0.792 | 0.06 |
| S5 | 0.634 | 0.177 |
| S6 | -0.811* | 0.05 |
| S7 | -0.831* | 0.04 |
| S8 | -0.864* | 0.026 |
| S9 | 0.063 | 0.906 |
| S10 | 0.921** | 0.009 |
| S11 | -0.464 | 0.354 |
| S12 | -0.065 | 0.903 |
| S13 | 0.481 | 0.334 |
| S14 | 0.328 | 0.526 |
| S15 | -0.52 | 0.29 |
| S16 | 0.488 | 0.326 |
| S17 | 0.696 | 0.125 |
| S18 | 0.223 | 0.671 |
| S19 | 0.931** | 0.007 |
| S20 | -0.727 | 0.102 |
| S21 | -0.724 | 0.104 |
| S22 | 0.962** | 0.002 |
| S23 | 0.947** | 0.004 |
*. were significantly related at the 0.05 level (bilateral). Significant correlation at the.01 level (double-sided).
As can be seen from table 5, the components S10, S19, S22 and S23 have very significant correlations with year (p <0.01), and the components S6, S7 and S8 have significant correlations with year (p < 0.05); meanwhile, the correlation between the components S4, S20 and S21 and different aging years is not obvious, but the Pearson correlation coefficients are respectively-0.792, -0.727 and-0.724, and the absolute values are all larger than 0.7, so that the three components have certain correlation with different aging years. Therefore, the above-mentioned 10 common components are intended to be included in the study category of the change rule of the year.
In order to further develop the change rule between the common components of the volatile oil in each pericarpium citri reticulatae sample and the aging year, the relative content of the 10 common components which are in certain correlation with the year is counted, and the result is shown in table 6. The common component S15 is 2- (methylamino) methyl benzoate, is a specific component of euryphylla pericarpium Citri Tangerinae, and can distinguish euryphylla pericarpium Citri Tangerinae from non-euryphylla pericarpium Citri Tangerinae.
TABLE 6 trend chart of relative content of common ingredients with certain correlation with year
As can be seen from table 6, the ingredients S4, S6, S7, S8, S20, S21 as a whole exhibited a tendency that their relative contents gradually decreased as the aging years increased; as can be seen from Table 5, the relative contents of 6 common components such as S4 are inversely related to the age. The components S10, S19, S22 and S23 have the tendency that the relative content thereof gradually increases with the age of aging; as can be seen from Table 5, the relative contents of 4 common components such as S10 are in direct correlation with the age.
5.2 analysis of the Change rules of the volatile oil composition and year
Firstly, the components which are negatively related to the year are used as molecules to be arranged and combined, and the number of the components in each molecular combination is 2 or more; the molecular combination generated by the arrangement and the year are subjected to linear trend simulation, and the results show that the trend of the 3 molecular combinations of the 'S4 + S7+ S8', 'S4 + S6+ S7+ S8', 'S4 + S6+ S7+ S20+ S8' is linearly reduced with the year (see Table 7), which indicates that the longer the aged years of the dried orange peel is, the lower the relative content of the volatile oil of the 3 molecular combinations is. Similarly, in the combinations of the constituents positively correlated with the year as the denominator, the trend of the 6 denominator combinations of "S10 + S19", "S10 + S22", "S10 + S22+ S23", "S10 + S19+ S22+ S23", "S10 + S19+ S22", "S10 + S19+ S23" with the year rising straight (see table 7) is found, indicating that the longer the year of aging the dried orange peel, the higher the relative content of the volatile oil in the 6 denominator combinations.
TABLE 7. ingredient combination summary table showing linear trend with year
Dividing three numerator combinations such as FZ 1-FZ 3 in the table 7 with six denominator combinations such as FM 1-FM 6 to obtain corresponding ratios; and then carrying out linear trend simulation on the ratio and the year. As a result, it was found that the ratio continuously decreased in a decreasing manner with the age of aging in 18 numbers, as shown in Table 8.
TABLE 8 summary of the combination ratios with the year in a continuously decreasing trend
As can be seen from tables 7 and 8, there is a certain rule of change between the volatile oil component in the citrus reticulata blanco and the year of aging, and in order to prove the feasibility of the rule presented by the above 18 ratios and the year, a verification sample (high quality) is introduced for verification in the next step to find out the optimal ratio.
6 authentication
Taking high-quality pericarpium Citri Tangerinae sample under item "2.2" as verification sample, determining volatile oil component index according to method under item "3 volatile oil component determination", and finding out common components identical to the above components S1-S23, the results are shown in Table 9.
TABLE 9. verify that the samples match the 23 common components of the assay sample (n. 2)
Note: nd, no detection
As can be seen from table 9, the 23 common components in the analysis sample were not present in all of the verification samples, but did not affect the verification results. According to the method under the item of '8.2 analysis of the change rule of volatile oil components and years', the verification sample and the analysis sample are put together for analysis, and the ratio (numerator combination/denominator combination) of the continuous descending or ascending trend with the years is counted, and the results are shown in the table 10.
TABLE 10 verification of the continuously decreasing ratio to year
| Serial number | Ratio of | M_6 | P_6 | P_9 | M_11 | M_12 | P_12 | M_14 | | P_24 | M_33 | |
| 1 | FZ2/FM2 | 325 | 310 | 271 | 242 | 130 | 108 | 98 | 81 | 44 | 14 | |
| 2 | FZ3/FM2 | 340 | 318 | 277 | 253 | 132 | 109 | 100 | 82 | 44 | 14 |
As can be seen from Table 10, the number of ratios of the samples of the citrus reticulata blanco through the source thereof, which are continuously decreasing with the year, is reduced from 18 to 2, i.e., "FZ 2/FM 2" and "FZ 3/FM 2" are ratios passing the verification.
As can be seen from tables 4 and 9, all the components in the verified 2 ratios have certain relative contents, which indicates that the components in the ratios can be detected.
From table 7, it can be seen that the denominator combinations in the 2 ratios are FM2(S10+ S22), while the numerator combinations differ from each other in that FZ3(S4+ S6+ S7+ S8+ S20) has 1 more component, S20, than FZ2(S4+ S6+ S7+ S8).
In order to further screen out the optimal ratio, the above 2 ratios "FZ 2/FM 2" and "FZ 3/FM 2" were analyzed year by year for seven components (S4, S6, S7, S8, S10, S20 and S22) involved in the analysis sample and the verification sample, and the results are shown in table 11.
TABLE 11 correlation analysis between 5 consensus components and year by validation
| Composition (I) | Pearson correlation | Both sides sigh |
| S4 | -0.809** | 0.005 |
| S6 | -0.734* | 0.016 |
| S7 | -0.798** | 0.006 |
| S8 | -0.809** | 0.005 |
| S10 | 0.936** | 0.000 |
| S20 | -0.705* | 0.023 |
| S22 | 0.679* | 0.031 |
*. were significantly related at the 0.05 level (bilateral). Significant correlation at the 0.01 level (bilateral).
It can be seen from table 11 that five components of S4, S6, S7, S20, S8 and the like all have significant correlation with the year (p <0.05), and it can be seen that the components in the 2 ratios obtained by adding the verification sample also meet the requirement that the volatile oil components of the analysis sample are included in the research category of the rules of change of the year, that is, the components participating in the combination have significant correlation with the year (p < 0.05).
The results show that 2 ratios of FZ2/FM2 and FZ3/FM2 in the volatile oil component combination can be suitable for researching the change rule between the years of aging.
7 screening of optimal discriminant models
7.1 Curve simulation
The aging years (X) are used as independent variables, the volatile oil ratios 'FZ 2/FM 2' and 'FZ 3/FM 2' in the table 10 are respectively used as dependent variables (Y), and SPSS19.0 software is adopted to respectively perform curve simulation on 11 models such as 'linear', 'logarithmic', 'reciprocal', 'quadratic', 'cubic', 'power', 'composite', 'S model', 'growth', 'exponential' and 'Logistic' on the above 2 ratios. The results of the 2 dependent variable curve equation models are shown in tables 12 and 13.
TABLE 12 model summary sum parameter estimates with dependent variable FZ2/FM2
TABLE 13 model summary sum parameter estimates with dependent variable FZ3/FM2
As can be seen from tables 12 and 13, the dependent variable is the coefficient R of each model equation of FZ2/FM22The coefficient of the ratio FZ2/FM2 is higher than that of FZ3/FM2 on the whole, which shows that the change rule of the ratio FZ2/FM2 and the year can reflect the real situation better. Therefore, the study will screen out the best discriminant model from the validated curve simulation of the ratio FZ2/FM2 versus year.
7.2 model screening
Preferentially selecting the curve with the highest correlation coefficient (R) from all curve simulation models; as can be seen from table 12, the coefficients of the "composite", "growth", "exponential" and "Logistic" models are the highest and consistent (r ═ 0.974). The corresponding equation expressions and simulation curve graphs of the four models are shown in table 14 and fig. 2.
TABLE 14 expression of four model equations
| Type of equation | Fang Cheng | Coefficient r |
| Compounding | Y＝613.555×0.893X | 0.974 |
| Increase in growth | Y＝e6.419-0.113X | 0.974 |
| Index of refraction | Y＝613.555×e-0.113X | 0.974 |
| Logistical | Y＝1/(1/μ+0.002×1.12X) | 0.974 |
Note: μ in the logistic equation is the upper limit value of the model.
From FIG. 16, it can be seen that the four fitting curves, "composite", "growth", "exponential" and "Logistic" are completely consistent; meanwhile, it is found that the four equation expressions in table 14 are the same function. Comprehensively considering the change rule of the function image corresponding to the above four equations, and finally changing the exponential equation Y to 613.555 × e-0.113X(r-0.974) as a model for discriminating the Xinhui dried orange peels in different aging years.
8 summary of the invention
Modern researches show that the factors influencing the dried orange peel volatile oil are many, including producing area, harvesting period, drying mode, storage condition, processing method and the like; for naturally aged pericarpium Citri Tangerinae, the change of volatile oil components is also influenced by storage conditions, but the influence on naturally aged pericarpium Citri Tangerinae of more than 5 years is small, and it is possible that the characteristic of pericarpium Citri Tangerinae at this stage tends to stable state and is not easily influenced by ambient environment. Therefore, in this example, the citrus chachiensis pericarpium aged naturally for more than 5 years is used as a research object to search the rule between the volatile oil component and the aging year.
As can be seen from tables 4 and 7, the verified ratios FZ2/FM2 include six compounds of the volatile oil components, i.e., S4(β -myrcene), S6 (d-limonene), S7(γ -terpinene), S8 (terpinolene), S10 (L-carveol), S22(2,6,11, 15-tetramethyl-hexadecane-2, 6,8,10, 14-pentaene), and the year identification models constructed from the six volatile oil components have accessibility.
Within the range of 5-33 years of aging, taking the aging year (X) as an independent variable and taking the volatile oil ratio 'FZ 2/FM 2' as a dependent variable (Y) to carry out curve model simulation, wherein the equation of the obtained optimal model is that Y is 613.555 × e-0.113XThe coefficient is as high as 0.974, and the fitting function is feasible and accurate as a discrimination model for discriminating the aging years of the citrus peel. However, whether the year discrimination model is suitable for the citrus chachiensis peels aged for less than 5 years and more than 33 years or not is still to be further verified for the citrus chachiensis peel samples of the corresponding aging years.
On the whole, the above embodiment of the invention takes citrus chachiensis peels aged naturally for more than 5 years as a research object, and the rule between the volatile oil component and the aging year is searched: firstly, extracting volatile components of dried orange peel analysis samples by adopting headspace-solid phase microextraction (HS-SPME), and separating, identifying and analyzing the volatile components of the dried orange peel in different storage years by gas chromatography-mass spectrometry (GC-MS); then, aiming at the common volatile oil components of the dried orange peel samples in each year, finding out the components which are obviously related to the year by adopting SPSS software, and carrying out linear trend analysis on the ratio and the year obtained by arranging and combining the negative related components as the numerator and the positive related components as the denominator; then, the ratio of the citrus peel samples from other sources to the continuous ascending or descending rule of the citrus peel samples to the year is verified, and meanwhile, the testability of the ratio molecules and the components contained in the denominator and the obvious correlation of the ratio molecules and the denominator are used as the optimal factors to be screened so as to obtain the optimal ratio; and finally, taking the aging year (X) as an independent variable, taking the optimal ratio (Y) as a dependent variable, adopting SPSS software to perform curve simulation of 11 models such as 'linear', 'logarithmic', 'reciprocal' and the like, and taking a curve with the highest relational number as a tangerine peel year distinguishing mode.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (12)
1. A method for identifying the age of citrus peel, said method comprising:
constructing an identification function model by using X and Y; wherein the content of the first and second substances,
the X is an aging year value;
the Y is the ratio of the content A to the content B,
the content A is the sum of the contents of the volatile oil components which are positively correlated with the aging year value,
the content B is the sum of the contents of the volatile oil components which are in negative correlation with the aging year value;
the volatile oil components positively correlated with the aging year value comprise beta-myrcene, dextro-limonene, gamma-terpinene and terpinolene, or comprise beta-myrcene, dextro-limonene, gamma-terpinolene, terpinolene and auraldehyde;
the volatile oil component which is negatively correlated with the aging year value comprises L-carveol and 2,6,11, 15-tetramethyl-hexadecane-2, 6,8,10, 14-pentaene;
and taking pericarpium citri reticulatae to be detected, detecting the content of the volatile oil component positively correlated with the aging year value and the content of the volatile oil component negatively correlated with the aging year value, and inputting the contents into the identification function model.
2. The method for identifying the aging year of pericarpium citri reticulatae according to claim 1, wherein the equation type of the identification function model is a complex equation, a growth equation, an exponential equation or a logistic equation.
3. The method of identifying the age of citrus peel according to claim 2, wherein the composite equation is: y613.555 × 0.893XR ═ 0.974; or/and the growth equation is: y ═ e6.419-0.113XR ═ 0.974; or/and the exponential equation is: y613.555 × e-0.113XR ═ 0.974; or/and the logistic equation is as follows: y1/(1/. mu. + 0.002X 1.12)X) μ is the upper limit of the function model, and R is 0.974.
4. The method for identifying the age of citrus peel according to any of claims 1 to 3, wherein the aging of the citrus peel is natural aging.
5. The method for identifying the age of citrus peel according to any one of claims 1 to 3, wherein the citrus peel is Potentilla aurantifolia.
6. The method for identifying the age of citrus peel according to any of the claims 1 to 3, wherein the age of the citrus peel is above 5 years; further, the aging period of the dried orange peel is 5 to 33 years.
7. The method for identifying the age of citrus peel according to any of the claims 1 to 3, characterized in that said detection comprises:
and extracting volatile oil components positively correlated with the aging year value and volatile oil components negatively correlated with the aging year value in the pericarpium citri reticulatae to be detected by headspace-solid phase microextraction, and analyzing the volatile oil components positively correlated with the aging year value and the volatile oil components negatively correlated with the aging year value by gas chromatography-mass spectrometry.
8. The method for identifying the age of citrus peel according to claim 7, wherein the headspace-solid phase microextraction employs an extraction temperature of 85 ℃ to 95 ℃.
9. The method of claim 7, wherein the pericarpium Citri Reticulatae to be tested is pre-treated as follows: taking the dried orange peel to be detected, and cutting into blocks.
10. The method for identifying the age of citrus peel according to claim 7, wherein the setting of the conditions of the gas chromatography comprises: adopting a temperature programming mode, keeping the initial temperature of the column at 45-55 ℃ for 1.8-2.2 min; raising the temperature to 68-72 ℃ at the speed of 2.8-3.2 ℃/min, and keeping the temperature for 8-12 min; raising the temperature to 108-112 ℃ at the speed of 7.8-8.2 ℃/min, and keeping the temperature for 4.5-5.5 min; raising the temperature to 208-212 ℃ at the speed of 3.8-4.2 ℃/min, and keeping the temperature for 1.8-2.2 min.
11. The method for identifying the age of citrus peel according to claim 10, wherein the setting of the conditions of the gas chromatograph further comprises:
a chromatographic column: HP-5MS (30 mm. times.0.25 μm);
carrier gas: he;
flow rate: 0.8mL/min to 1.2 mL/min;
sample inlet temperature: 220 to 240 ℃;
the split ratio is as follows: (28-32): 1.
12. The method for identifying the age of dried orange peel according to any one of claims 8 to 11, wherein the condition setting of the mass spectrum comprises:
ion source temperature: 225-235 ℃;
electron energy: 68eV to 72 eV;
ion collection range: 35m/z to 450 m/z.
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