CN112595691B - Method for establishing and quantitatively analyzing characteristic components of lavender essential oil based on near infrared Raman spectrum fusion - Google Patents
Method for establishing and quantitatively analyzing characteristic components of lavender essential oil based on near infrared Raman spectrum fusion Download PDFInfo
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- 244000178870 Lavandula angustifolia Species 0.000 title claims abstract description 130
- 235000010663 Lavandula angustifolia Nutrition 0.000 title claims abstract description 130
- 239000001102 lavandula vera Substances 0.000 title claims abstract description 129
- 235000018219 lavender Nutrition 0.000 title claims abstract description 129
- 239000000341 volatile oil Substances 0.000 title claims abstract description 109
- 238000001228 spectrum Methods 0.000 title claims abstract description 85
- 238000000034 method Methods 0.000 title claims abstract description 71
- 230000004927 fusion Effects 0.000 title claims abstract description 64
- 238000002095 near-infrared Raman spectroscopy Methods 0.000 title claims abstract description 8
- 238000001237 Raman spectrum Methods 0.000 claims abstract description 91
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 81
- 238000012937 correction Methods 0.000 claims abstract description 70
- 238000004445 quantitative analysis Methods 0.000 claims abstract description 40
- 238000010606 normalization Methods 0.000 claims abstract description 29
- 238000004817 gas chromatography Methods 0.000 claims abstract description 13
- CDOSHBSSFJOMGT-UHFFFAOYSA-N linalool Chemical compound CC(C)=CCCC(C)(O)C=C CDOSHBSSFJOMGT-UHFFFAOYSA-N 0.000 claims description 40
- UWKAYLJWKGQEPM-LBPRGKRZSA-N linalyl acetate Chemical compound CC(C)=CCC[C@](C)(C=C)OC(C)=O UWKAYLJWKGQEPM-LBPRGKRZSA-N 0.000 claims description 38
- UWKAYLJWKGQEPM-UHFFFAOYSA-N linalool acetate Natural products CC(C)=CCCC(C)(C=C)OC(C)=O UWKAYLJWKGQEPM-UHFFFAOYSA-N 0.000 claims description 21
- 239000001490 (3R)-3,7-dimethylocta-1,6-dien-3-ol Substances 0.000 claims description 20
- CDOSHBSSFJOMGT-JTQLQIEISA-N (R)-linalool Natural products CC(C)=CCC[C@@](C)(O)C=C CDOSHBSSFJOMGT-JTQLQIEISA-N 0.000 claims description 20
- QTBSBXVTEAMEQO-UHFFFAOYSA-M Acetate Chemical compound CC([O-])=O QTBSBXVTEAMEQO-UHFFFAOYSA-M 0.000 claims description 20
- 229930007744 linalool Natural products 0.000 claims description 20
- 238000012795 verification Methods 0.000 claims description 18
- 238000001069 Raman spectroscopy Methods 0.000 claims description 17
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- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 1
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
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- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/65—Raman scattering
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Abstract
The invention provides a method for establishing a lavender essential oil characteristic component quantitative analysis model based on near infrared Raman spectrum fusion and a quantitative analysis method, which specifically comprises the following steps: (1) collecting a sample of lavender essential oil; (2) Obtaining characteristic and representative component percentage contents of a lavender essential oil sample according to gas chromatography in a national standard; (3) Collecting near infrared light and Raman spectrum diagrams of a lavender essential oil sample, and carrying out baseline correction and vector normalization treatment on the measured near infrared light and Raman spectrum diagrams; (4) And fusing the spectra of the near infrared spectrum and the Raman spectrum in a spectrum parallel mode, and sharing the same coordinate. (5) establishing a partial least square quantitative correction model; (6) And (3) measuring a lavender essential oil sample by adopting the established quantitative analysis model. The method for quantitatively analyzing the quality of the lavender essential oil is simple and convenient to operate, accurate, time-saving and efficient.
Description
Technical Field
The invention relates to the technical field of determination of characteristic component content of lavender essential oil, in particular to a method for establishing a quantitative analysis model of characteristic component of lavender essential oil based on near infrared Raman spectrum fusion and a quantitative analysis method.
Background
The lavender essential oil is volatile oil extracted from fresh inflorescence of Lavender (Lavandula angustifolia Mill.) belonging to Labiatae by steam distillation, and has multiple effects of tranquilizing, antidepressant, sleep improving, digestion promoting, and pathogenic wind dispelling. The lavender essential oil is a complex mixture composed of a plurality of different types of aromatic compounds, wherein the proportion of the different compounds directly influences the quality of the lavender essential oil, the content of characteristic components in the lavender essential oil is measured by using a gas chromatography in the national standard of the lavender essential oil, and the qualification range of the representative and characteristic component content (w/%) in the lavender essential oil is as follows: 20% -43% of linalool; 25% -47% of linalyl acetate; lavender acetate is less than or equal to 8%.
At present, methods for measuring chemical components of lavender essential oil mainly comprise gas chromatography and gas chromatography-mass spectrometry, but the methods are time-consuming and difficult to realize rapid quantitative detection in a large scale.
In view of this, the present invention has been made.
Disclosure of Invention
The invention aims at providing a method for establishing a lavender essential oil characteristic component quantitative analysis model.
The second purpose of the invention is to provide a quantitative analysis method for characteristic components of lavender essential oil, which can rapidly and accurately measure the contents of various characteristic components of the lavender essential oil.
In order to achieve the above object of the present invention, the following technical solutions are specifically adopted:
In a first aspect, the invention provides a method for establishing a lavender essential oil characteristic component quantitative analysis model, which comprises the following steps:
Collecting a near infrared spectrum chart and a Raman spectrum chart of a lavender essential oil sample;
Fusing the near infrared spectrogram and the Raman spectrogram to obtain a fused spectrogram;
preprocessing the fusion spectrogram to obtain a preprocessed fusion spectrogram;
Establishing a quantitative analysis model between linalool, linalyl acetate, lavender acetate content and near infrared Raman fusion spectrum of a lavender essential oil sample by adopting a partial least square method;
and evaluating and checking the quantitative analysis model to obtain an optimized quantitative analysis model.
Further, the establishing method further comprises: collecting a near infrared spectrum and a Raman spectrum of a lavender essential oil sample, performing baseline correction and vector normalization on the near infrared spectrum and the Raman spectrum to obtain a preprocessed near infrared spectrum and a preprocessed Raman spectrum, and then fusing the preprocessed near infrared spectrum and the preprocessed Raman spectrum;
Or the establishing method further comprises the following steps: after collecting a near infrared spectrum of a lavender essential oil sample, carrying out baseline correction and vector normalization treatment on the near infrared spectrum to obtain a preprocessed near infrared spectrum; after collecting a Raman spectrum of a lavender essential oil sample, carrying out baseline correction and vector normalization processing on the Raman spectrum to obtain a pretreated Raman spectrum; and then fusing the preprocessed near infrared spectrum and the preprocessed Raman spectrum.
Further, the lavender essential oil sample is from the region of the Yili of Xinjiang, all samples are divided into a correction set sample and a verification set sample, the correction set sample is used for establishing a correction model, and the verification set sample is used for verifying the model.
Further, a transmission mode is used for collecting a near infrared spectrogram, a quartz cuvette with an optical path of 1mm is selected, the ambient temperature is 22 ℃, the scanning range is 4000cm -1～6600cm-1, the resolution is 8cm -1, the scanning accumulation times are 32 times, background scanning is firstly carried out, then lavender essential oil samples are measured under the same experimental condition, each sample is measured for 3 times in parallel, and the average value is obtained;
preferably, a laser with 532nm wavelength is adopted for Raman spectrum graph acquisition, the laser power is 100mW, the environment temperature is 22 ℃, after the lavender essential oil is adsorbed by a glass capillary, spectrum data are obtained by measuring 3s under a 50X objective lens, the spectrum acquisition range is 600cm -1～3200cm-1, each sample is tested three times, the average value is taken, and the average spectrum is taken as an analysis spectrum.
Further, fusing the near infrared spectrogram and the raman spectrogram includes:
the spectra are fused in a spectrum parallel mode, the same coordinate is shared, the abscissa of the fused spectrogram is a spectrum channel, and the ordinate of the fused spectrogram is the sum intensity value of the parallel spectra.
Further, the preprocessing method of the fusion spectrogram comprises a first derivative, a multi-element scattering correction or a standard normal transformation;
Preferably, the first derivative pretreatment is performed on the fusion spectrogram to obtain a first derivative graph of the fusion spectrum.
Further, evaluating and checking the quantitative analysis model includes:
Taking a measurement coefficient R 2 between a predicted value and a reference value of a correction set, a cross validation mean square error (RMSECV) of the correction set and a correction standard deviation RMSEC as model evaluation indexes to evaluate the rationality of the model;
The performance of the model is measured by a validation set sample, and the prediction performance of the model is measured by a prediction standard deviation RESEP and a prediction set measurement coefficient Rp 2.
Further, the determination method of linalool, linalyl acetate and lavender acetate content of the lavender essential oil sample is a gas chromatography method in GB/T12653-2008 Chinese lavender (essential oil);
Preferably, the chromatographic conditions of the gas chromatography include:
chromatographic column: RTX-50MS quartz capillary column;
Programming temperature: keeping at 50deg.C for 5min, and keeping at 2deg.C/min -1 to 100deg.C, 3deg.C/min -1 to 150deg.C, 8deg.C/min -1 to 250deg.C for 5min;
The carrier gas flow rate was 1.16mL min -1, and the pressure was 65.2KPa.
In a second aspect, the invention provides a method for quantitatively analyzing characteristic components of lavender essential oil, which is used for collecting a near infrared spectrum chart and a Raman spectrum chart of a lavender essential oil sample to be tested;
Fusing the near infrared spectrogram and the Raman spectrogram to obtain a fused spectrogram;
preprocessing the fusion spectrogram to obtain a preprocessed fusion spectrogram;
constructing a quantitative analysis model by using the establishment method;
Substituting the fusion spectrogram of the lavender essential oil sample to be detected after pretreatment into a constructed quantitative analysis model, and predicting the linalool, linalyl acetate and lavender acetate content of the lavender essential oil sample to be detected.
Further, the quantitative analysis method further comprises: collecting a near infrared spectrum and a Raman spectrum of a lavender essential oil sample, performing baseline correction and vector normalization on the near infrared spectrum and the Raman spectrum to obtain a preprocessed near infrared spectrum and a preprocessed Raman spectrum, and then fusing the preprocessed near infrared spectrum and the preprocessed Raman spectrum;
Or the quantitative analysis method further comprises: after collecting a near infrared spectrum of a lavender essential oil sample, carrying out baseline correction and vector normalization treatment on the near infrared spectrum to obtain a preprocessed near infrared spectrum; after collecting a Raman spectrum of a lavender essential oil sample, carrying out baseline correction and vector normalization processing on the Raman spectrum to obtain a pretreated Raman spectrum; and then fusing the preprocessed near infrared spectrum and the preprocessed Raman spectrum.
Preferably, the first derivative pretreatment is performed on the fusion spectrogram to obtain a first derivative graph of the fusion spectrum.
The method for establishing the quantitative analysis model of the characteristic components of the lavender essential oil and the quantitative analysis method provided by the invention have at least the following beneficial effects:
According to the invention, a near infrared spectrum and Raman spectrum fusion technology is selected, so that the problems that the traditional gas chromatography is time-consuming and difficult to detect in a large scale in actual production can be solved, and the near infrared spectrum and the Raman spectrum have strong complementarity, so that the obtained fusion spectrum information is comprehensive, and the chemical information of lavender essential oil can be more comprehensively embodied.
Compared with the traditional gas chromatography and gas chromatography mass spectrometry, the method can obtain the analysis result within a few minutes without sample treatment, and greatly improves the analysis efficiency. The method has the advantages of good robustness, fitting degree and high prediction precision, can rapidly determine the content of the main component in the lavender essential oil, and provides a rapid and accurate measuring method which is simple, convenient and feasible and is easy to popularize and apply for rapid quantitative analysis of the lavender essential oil.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for quantitatively analyzing characteristic components of lavender essential oil of the present invention;
FIG. 2 is a diagram of the near infrared spectrum of the lavender essential oil and a diagram of the near infrared spectrum after vector normalization (a: near infrared spectrum, b: diagram after vector normalization);
FIG. 3 is a Raman spectrum of the lavender essential oil of the example and a Raman spectrum after vector normalization (a: raman spectrum, b: spectrum after vector normalization);
FIG. 4 is a graph of the fusion spectrum of the near infrared Raman parallel addition after vector normalization in the examples;
FIG. 5 is a graph of the fusion spectra obtained using three different preprocessing methods (a: first derivative, lst Der, b: multiple scatter correction, MSC, c: standard normal transformation, SNV);
FIG. 6 is a correlation between predicted values of fusion spectra of samples of a correction set and GC-MS measurements for the PLS model of example (a: linalool, b: linalyl acetate, c: lavender acetate);
FIG. 7 is a graph showing the correlation between predicted results and GC-MS measurements for samples of a sample of a verification set of lavender essential oil of the example (a: linalool, b: linalyl acetate, c: lavender acetate).
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
At present, the methods for measuring the chemical components of the lavender essential oil mainly comprise a gas chromatography method and a gas chromatography-mass spectrometry combined method, but the methods are time-consuming and difficult to realize rapid quantitative detection in a large scale, and the near infrared spectrum and Raman spectrum analysis technology has the advantages of rapid analysis speed, short analysis time, non-destructiveness, no chemical pollution, no need of complex sample treatment process, low cost, easy realization of online detection and the like, is particularly suitable for mass sample testing, and is widely applied to quality detection in the fields of agriculture, food industry, chemical industry, medicine industry and the like, and becomes a modern technology for rapid analysis.
The Near Infrared (NIR) obtains the characteristic information of the combined frequency and the frequency multiplication of the vibration of the hydrogen-containing group of the detected organic molecule, and the spectrum overlapping degree of the NIR is higher. RAMAN spectrum (RAMAN) gives RAMAN scattering intensity of the measured organic matter with low spectral overlap. Unlike near infrared spectra, both polar and nonpolar molecules can produce raman spectra, and the obtained information has strong complementarity with near infrared spectra.
According to the invention, the near infrared absorption spectrum and the Raman scattering spectrum of the lavender essential oil are respectively measured, and after certain data pretreatment and spectral band screening, the near infrared spectrum and the Raman spectrum are subjected to spectral data accumulation fusion. Compared with a single Raman spectrum and near infrared spectrum, the data after spectrum fusion can more comprehensively reflect the chemical information of the lavender essential oil, so that a method for measuring the contents of various characteristic components of the lavender essential oil based on the NIR and RAMAN spectrum fusion technology is established.
The near infrared spectrometry and the Raman spectrometry are both quick analysis methods, can realize on-site and on-line analysis, can complete the measurement of multiple characteristic components of the lavender essential oil by only collecting and measuring the near infrared spectrum and the Raman spectrum of a measured sample within a few minutes, and the measurement process does not need complex pretreatment process and chemical reagent.
As shown in fig. 1, the invention provides a method (quantitative analysis method) for determining the contents of various characteristic components (mainly linalool, linalyl acetate and lavender acetate) of lavender essential oil based on near infrared and raman spectrum fusion technology, which comprises the following steps:
and step 1, selecting a lavender essential oil sample to be measured (a sample to be measured).
The source of the lavender essential oil sample is not limited, and is preferably from the region of the illipe xinjiang.
Step 2, spectrum measurement: and (3) measuring a near infrared spectrum and a Raman spectrum of the lavender essential oil sample in the step (1).
In a preferred embodiment, near infrared spectrum acquisition uses a transmission mode, a quartz cuvette with an optical path of 1mm is selected, the ambient temperature is 22 ℃, the scanning range is 4000cm -1～6600cm-1, the resolution is 8cm -1, the number of times of scanning accumulation is 32, background scanning is carried out firstly, then lavender essential oil samples are measured under the same experimental conditions, each sample is measured 3 times in parallel, and the average value is obtained.
In a preferred embodiment, the raman spectroscopy is performed using a 532nm wavelength laser with a laser power of 100mW and an ambient temperature of 22 ℃, the lavender essential oil in step 1 is adsorbed by a 0.3mm×10mm glass capillary, and then the spectroscopic data is obtained by measuring for 3s under a 50×objective lens, the spectrum acquisition range is 600cm -1～3200cm-1, and each sample is tested three times, averaged, and the average spectrum is taken as the analysis spectrum.
And step 3, preprocessing the near infrared spectrogram and the Raman spectrogram obtained in the step 2.
In a preferred embodiment, the near infrared spectrum and the raman spectrum are subjected to baseline correction and vector normalization treatment, background interference is eliminated, and the longitudinal coordinate values of the near infrared spectrum and the raman spectrum are in the same order of magnitude, so that the near infrared spectrum and the raman spectrum after the pretreatment of the lavender essential oil sample are obtained.
After the near infrared spectrum and the Raman spectrum are subjected to baseline correction, the ordinate of the near infrared spectrum is an absorption intensity value, the ordinate of the Raman spectrum is a Raman scattering intensity value, the near infrared spectrum and the Raman spectrum are greatly different, and vector normalization processing is performed to eliminate the inconsistency of the ordinate units of the near infrared spectrum and the Raman spectrum, so that the ordinate values of the near infrared spectrum and the Raman spectrum are in the same order.
The specific baseline correction and vector normalization processes may be performed in a conventional manner.
It should be noted that the pretreatment may be performed uniformly after obtaining both the near infrared spectrum and the raman spectrum, or may be performed after obtaining separate spectra (near infrared spectrum pretreatment is performed after obtaining the near infrared spectrum, and raman spectrum pretreatment is performed after obtaining the raman spectrum).
Step 4, spectrum fusion: and (3) fusing the near infrared spectrum and the Raman spectrum which are preprocessed in the step (3).
In a preferred embodiment, spectra are fused in a spectrally parallel fashion, sharing the same coordinate. The abscissa of the fusion spectrum is a spectrum channel, and the ordinate of the fusion spectrum is the sum intensity value of the parallel spectrum.
The spectral parallel mode refers to the summation of near infrared and raman spectral data.
Parallel spectra refer to near infrared spectra and raman spectra.
The near infrared spectrum range is: 4000cm -1～6600cm-1 and a Raman spectrum ranging from 600cm -1～3200cm-1. One data point is taken from low wave number to high wave number every 4cm -1, at this time, the number of data channels of near infrared and Raman spectra is 650, and the weight ratio of near infrared and Raman spectra is 1 during fusion: 1, a parallel fusion method is adopted, the near infrared spectrum and the Raman spectrum are added to the data on the same channel to obtain new fusion data, at the moment, the abscissa is the spectrum channel 1-650, the ordinate is the data addition value of the near infrared spectrum and the Raman spectrum, and the characteristic information of chemical components contained in the fused spectrum data is more abundant.
Step 5, fusion spectrum pretreatment: and (3) preprocessing the fusion spectrogram obtained in the step (4).
The pretreatment method uses first derivative (FIRST DERIVATIVES, lst Der), multiple scatter correction (Multiplicative scatter correction, MSC), standard normal transformation (Standard normal variate, SNV) for screening.
And obtaining an optimized fusion spectrum pretreatment method which is a first derivative method through the model evaluation index.
In a preferred embodiment, the first derivative pretreatment is performed on the fusion spectrum to obtain a first derivative graph of the lavender essential oil sample fusion spectrum.
Step 6, predicting the content of characteristic components in the lavender essential oil sample: and (3) predicting the contents of linalool, linalyl acetate and lavender acetate which are characteristic components of the selected lavender essential oil sample by adopting an optimized quantitative analysis model for the lavender essential oil fusion spectrogram obtained in the step (5).
The method for establishing the optimized quantitative analysis model comprises the following steps:
and a step a, collecting a representative lavender essential oil sample.
Samples of lavender essential oil were all from the region of the illipe xinjiang.
All samples are divided into a correction set sample and a verification set sample, wherein the correction set sample is used for establishing a correction model, and the verification set sample is used for verifying the model.
And (3) selecting a correction set sample by uniformly distributing the contents of linalool, linalyl acetate and lavender acetate, establishing a quantitative analysis correction model, and externally verifying the model by taking the remaining samples as verification sets.
And b, collecting a near infrared spectrum chart and a Raman spectrum chart of the lavender essential oil sample, wherein the spectrum collection conditions are the same as those in the step 2. Namely:
in a preferred embodiment, near infrared spectrum acquisition uses a transmission mode, a quartz cuvette with an optical path of 1mm is selected, the ambient temperature is 22 ℃, the scanning range is 4000cm -1～6600cm-1, the resolution is 8cm -1, the number of times of scanning accumulation is 32, background scanning is carried out firstly, then lavender essential oil samples are measured under the same experimental conditions, each sample is measured 3 times in parallel, and the average value is obtained.
In a preferred embodiment, the raman spectroscopy is performed using a 532nm wavelength laser with a laser power of 100mW and an ambient temperature of 22 ℃, the lavender essential oil in step 1 is adsorbed by a 0.3mm×10mm glass capillary, and then the spectroscopic data is obtained by measuring for 3s under a 50×objective lens, the spectrum acquisition range is 600cm -1～3200cm-1, and each sample is tested three times, averaged, and the average spectrum is taken as the analysis spectrum.
And c, carrying out baseline correction and vector normalization pretreatment on all the measured near infrared spectrograms and the measured Raman spectrograms of the samples to eliminate background interference and inconsistency of near infrared and Raman spectrum intensities, wherein the baseline correction and vector normalization pretreatment are the same as that of the step 3, and are not repeated here.
And d, fusing the preprocessed near infrared spectrogram and the preprocessed Raman spectrogram, fusing the spectrums in a spectrum parallel mode, sharing the same coordinate, wherein the abscissa of the fused spectrum is a spectrum channel, the ordinate of the fused spectrum is the sum intensity value of the parallel spectrum, and the fusion is the same as that in the step 4, and is not repeated here.
And e, preprocessing the fusion spectrum data of the lavender essential oil sample.
The preprocessing method adopts a first derivative (FIRST DERIVATIVES, lst Der), multiple scattering correction (Multiplicative scatter correction, MSC) and standard normal transformation (Standard normal variate, SNV) to screen, and the fusion spectrum optimization preprocessing method is the first derivative method.
And f, establishing a quantitative analysis correction model between linalool, linalyl acetate, percentage of lavender acetate (w/%) and a fusion spectrum of the lavender essential oil sample by adopting a Partial Least Squares (PLS).
And correlating the fusion spectrum of the correction set sample with the characteristic component content of the lavender essential oil by a partial least square method, and respectively establishing quantitative analysis models of linalool, linalyl acetate and lavender acetate. And obtaining the correlation between the predicted value of the percentage content of linalool, linalyl acetate and lavender acetate in the samples of the correction set and the verification set and the control value.
In a preferred embodiment, the content of linalool, linalyl acetate, lavender acetate in all samples of lavender essential oil was determined as control value by gas chromatography in "GB/T12653-2008 chinese lavender (essential oil)".
The gas chromatography measurement adopts an RTX-50MS quartz capillary column (30 m multiplied by 0.25 mm) chromatographic column; programming temperature: keeping at 50deg.C for 5min, and keeping at 2deg.C/min -1 to 100deg.C, 3deg.C/min -1 to 150deg.C, 8deg.C/min -1 to 250deg.C for 5min; carrier gas (99.999% he) flow rate was 1.16ml·min -1, pressure 65.2KPa.
And g, evaluating and checking the quantitative analysis correction model to obtain an optimized quantitative analysis model.
The PLS quantitative analysis model is established by taking a measurement coefficient R 2 between a predicted value and a reference value of a correction set, a correction set cross-Validation mean square error (Root Mean Square Error of Cross-Validation, RMSECV) and a correction standard deviation (Root Mean Square of Calibration, RMSEC) as model evaluation indexes, wherein the closer R 2 is to 1, the smaller the RMSECV is, and the RMSEC is, so that the more reasonable the correction model is established.
And (3) carrying out inspection and evaluation on the model by using an external verification method, measuring the prediction performance of the model by using a verification set sample, measuring the prediction performance of the model by using a prediction standard deviation (Root Mean Square Error of Prediction, RESEP) and a prediction set measurement coefficient Rp 2, and obtaining the optimized quantitative analysis model after the prediction standard deviation and the prediction set measurement coefficient Rp 2 are matched.
The process of the model construction method can be summarized as follows:
A correction set is formed by selecting a sufficient number of representative lavender essential oil samples, the content of characteristic components of the samples is measured by using the current national standard method as a control value, then the near infrared spectrum and the Raman spectrum of the samples are measured, and after the spectrum data are subjected to baseline correction and vector normalization treatment, parallel accumulation fusion is carried out on the near infrared spectrum data and the Raman spectrum data. And (3) establishing a quantitative analysis model between the fusion spectrum information and the characteristic component content of the lavender essential oil by adopting a chemometric algorithm of Partial Least Squares (PLS). A verification set is formed by a group of samples with known lavender essential oil characteristic component content, near infrared and Raman spectra of the verification set samples are measured, baseline correction and vector normalization processing are carried out, parallel data are carried out to form a verification set fusion spectrum, and the content of the corresponding lavender essential oil characteristic component is calculated by an established model, so that verification evaluation is carried out on the modeled model. If the deviation of the validation set is within an acceptable range, the model can be used for the determination of unknown samples.
The invention is further illustrated by the following examples. The materials in the examples were prepared according to the existing methods or were directly commercially available unless otherwise specified.
Examples
1. The lavender essential oil samples were collected, 100 lavender essential oil samples were obtained from the region of the illipe in Xinjiang, and were divided into 70 correction set samples, 30 correction set samples for use in establishing a correction model, and verification set samples for use in verifying models, and finally the characteristic component content distribution of the correction set and verification set samples is shown in table 1 below.
Table 1 distribution of the characteristic components of lavender essential oil in percentage
2. Instrument for measuring and controlling the intensity of light
Fourier transform near infrared spectrometer: BRUKER company VERTEX; laser raman spectrometer: HORBIA company LabRAM HR Evolution; gas chromatograph: agilent Technologies,5890.
3. Spectrum acquisition and pretreatment
3.1 Near infrared Spectrum acquisition and pretreatment
Using a transmission mode, selecting a quartz cuvette with an optical path of 1mm, performing background scanning for 32 times at an ambient temperature of 22 ℃ and a scanning range of 4000cm -1～6600cm-1 and a resolution of 8cm -1, measuring lavender essential oil samples under the same experimental conditions in parallel for 3 times, taking an average value, performing baseline correction and vector normalization pretreatment, and performing near infrared spectrum and vector normalization treatment, wherein the figure 2 is shown.
3.2 Raman Spectroscopy acquisition and pretreatment
The Lavender essential oil in the step 1 is absorbed by a glass capillary tube with the temperature of 0.3mm multiplied by 10mm by adopting a laser with the wavelength of 532nm, the laser power is 100mW, the ambient temperature is 22 ℃, the spectrum data are obtained by measuring 3s under a 50 multiplied by objective lens, the spectrum acquisition range is 600cm -1～3200cm-1, each sample is tested three times, the average value is taken, the average spectrum is taken as an analysis spectrum, the baseline correction and the vector normalization pretreatment are carried out, and the Raman spectrum and the vector normalization treatment are carried out later, and then the figure 3 is shown.
4. Spectral fusion
The preprocessed near infrared spectrum and Raman spectrum are fused, the spectrum fusion is parallel accumulation fusion of near infrared spectrum data and Raman spectrum data, and the near infrared spectrum range is as follows: 4000cm -1～6600cm-1 and a Raman spectrum ranging from 600cm -1～3200cm-1. One data point is taken from low wave number to high wave number every 4cm -1, at this time, the number of data channels of near infrared and Raman spectra is 650, and the weight ratio of near infrared and Raman spectra is 1 during fusion: 1, a parallel fusion method is adopted to sum the data on the same channel by the near infrared spectrum and the Raman spectrum to obtain new fusion data, at the moment, the abscissa is the spectrum channel 1-650, and the ordinate is the data sum value of the near infrared spectrum and the Raman spectrum, and obviously, the characteristic information of chemical components contained in the fused spectrum data is more abundant. The spectrum after fusion is shown in FIG. 4.
5. Correction model creation
5.1 Determination of the characteristic value content of the Lavender essential oil sample
The content (w/%) of linalool, linalyl acetate, and lavender acetate in all samples of lavender essential oil was determined as control values by gas chromatography in "GB/T12653-2008 chinese lavender (essential oil)".
Chromatographic conditions chromatographic column: RTX-50MS quartz capillary column (30 m 0.25 mm); programming temperature: keeping at 50deg.C for 5min, and keeping at 2deg.C/min -1 to 100deg.C, 3deg.C/min -1 to 150deg.C, 8deg.C/min -1 to 250deg.C for 5min; carrier gas (99.999% he) flow rate was 1.16ml·min -1, pressure 65.2KPa.
5.2 Establishment of quantitative analysis model
Firstly, preprocessing the near infrared Raman fusion spectrum of the lavender essential oil by adopting the following three methods: the first derivative (FIRST DERIVATIVES, lst Der), the multiple scatter correction (Multiplicative scatter correction, MSC), the standard normal transformation (Standard normal variate, SNV), the three preprocessed fusion spectra are shown in FIG. 5, and finally the fusion spectrum preprocessing method with the optimized first derivative is preferred (see Table 2).
And (3) establishing a quantitative correction model between linalool, linalyl acetate, the percentage of lavender acetate (w/%) and the fusion spectrum of the lavender essential oil sample by adopting a partial least squares method (PLS), measuring a coefficient R 2 between a predicted value and a reference value of a correction set, and performing cross Validation on a mean square error (Root Mean Square Error of Cross-Validation, RMSECV) of the correction set, wherein a correction standard deviation (Root Mean Square of Calibration, RMSEC) is used as a model evaluation index, and the closer R 2 is to 1, the smaller the RMSECV is and the smaller the RMSEC is, so that the more reasonable the correction model is established. External validation was performed with validation set samples to measure the performance of the model, and the predicted performance of the model was measured by prediction standard deviation (Root Mean Square Error of Prediction, RESEP), and predictor determination coefficient Rp 2, with closer Rp 2 to 1, smaller RMSEP, indicating more accurate model prediction (see table 2). The correlation graphs of the model on the percentage content predicted values of linalool, linalyl acetate and lavender acetate in the correction set and verification set samples and the comparison values measured by gas chromatography mass spectrometry are shown in fig. 6 and 7 respectively. The analysis result of the percentage content (w/%) of linalool, linalyl acetate and lavender acetate of the lavender essential oil sample can be obtained rapidly by the method. The built NIR-RAMAN-PLS fusion spectrum quantitative analysis model has good robustness, high fitting degree and high prediction precision, can rapidly determine the content of main components in the lavender essential oil, and provides a simple and rapid measurement method for rapid quantitative analysis of the lavender essential oil.
TABLE 2 Lavender essential oil characteristic component quantitative correction model and validation results
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (10)
1. The method for establishing the lavender essential oil characteristic component quantitative analysis model is characterized by comprising the following steps of:
Collecting a near infrared spectrum chart and a Raman spectrum chart of a lavender essential oil sample;
Fusing the near infrared spectrogram and the Raman spectrogram to obtain a fused spectrogram;
preprocessing the fusion spectrogram to obtain a preprocessed fusion spectrogram;
Establishing a quantitative analysis model between linalool, linalyl acetate, lavender acetate content and near infrared Raman fusion spectrum of a lavender essential oil sample by adopting a partial least square method;
evaluating and checking the quantitative analysis model to obtain an optimized quantitative analysis model;
The near infrared spectrum range is: 4000cm -1～6600cm-1, raman spectrum range from 600cm -1～3200cm-1, from low wave number to high wave number, taking one data point every 4cm -1, wherein the number of data channels of near infrared spectrum and Raman spectrum is 650, and the weight ratio of near infrared spectrum and Raman spectrum is 1:1 during fusion;
the preprocessing method of the fusion spectrogram comprises the steps of preprocessing the first derivative of the fusion spectrogram to obtain the first derivative graph of the fusion spectrum;
Dividing the sample into a correction set sample and a verification set sample, wherein the correction set sample is used for establishing a correction model, and the verification set sample is used for verifying the model;
evaluation and testing of the quantitative analytical model included:
Taking a measurement coefficient R 2 between a predicted value and a reference value of a correction set, a cross validation mean square error (RMSECV) of the correction set and a correction standard deviation RMSEC as model evaluation indexes to evaluate the rationality of the model;
The performance of the model is measured by a validation set sample, and the prediction performance of the model is measured by a prediction standard deviation RESEP and a prediction set measurement coefficient Rp 2.
2. The method of establishing according to claim 1, further comprising: collecting a near infrared spectrum and a Raman spectrum of a lavender essential oil sample, performing baseline correction and vector normalization on the near infrared spectrum and the Raman spectrum to obtain a preprocessed near infrared spectrum and a preprocessed Raman spectrum, and then fusing the preprocessed near infrared spectrum and the preprocessed Raman spectrum;
Or the establishing method further comprises the following steps: after collecting a near infrared spectrum of a lavender essential oil sample, carrying out baseline correction and vector normalization treatment on the near infrared spectrum to obtain a preprocessed near infrared spectrum; after collecting a Raman spectrum of a lavender essential oil sample, carrying out baseline correction and vector normalization processing on the Raman spectrum to obtain a pretreated Raman spectrum; and then fusing the preprocessed near infrared spectrum and the preprocessed Raman spectrum.
3. The method according to claim 1 or 2, wherein the near infrared spectrum is collected by using a transmission mode, a quartz cuvette with an optical path of 1mm is selected, the ambient temperature is 22 ℃, the scanning range is 4000cm -1～6600cm-1, the resolution is 8cm -1, the number of times of scanning accumulation is 32, background scanning is performed first, then the lavender essential oil samples are measured under the same experimental conditions, each sample is measured 3 times in parallel, and the average value is obtained.
4. The method according to claim 1 or 2, wherein the raman spectrum is collected by using a 532nm wavelength laser with a laser power of 100mW and an ambient temperature of 22 ℃, the lavender essential oil is adsorbed by a glass capillary, and the spectrum data is obtained by measuring 3s under a 50 x objective lens, the spectrum collection range is 600cm -1～3200cm-1, and each sample is tested three times, averaged, and the average spectrum is used as the analysis spectrum.
5. The method according to claim 1 or 2, wherein fusing the near infrared spectrogram and the raman spectrogram comprises:
the spectra are fused in a spectrum parallel mode, the same coordinate is shared, the abscissa of the fused spectrogram is a spectrum channel, and the ordinate of the fused spectrogram is the sum intensity value of the parallel spectra.
6. The method for establishing the lavender essential oil according to claim 1 or 2, wherein the determination method of linalool, linalool acetate and lavender acetate content of the lavender essential oil sample is a gas chromatography method in GB/T12653-2008 Chinese lavender (essential oil).
7. The method of establishing according to claim 6, wherein the chromatographic conditions of the gas chromatography method include:
chromatographic column: RTX-50MS quartz capillary column;
Programming temperature: keeping at 50deg.C for 5min, and keeping at 2deg.C/min -1 to 100deg.C, 3deg.C/min -1 to 150deg.C, 8deg.C/min -1 to 250deg.C for 5min;
The carrier gas flow rate was 1.16mL min -1, and the pressure was 65.2KPa.
8. The quantitative analysis method for the characteristic components of the lavender essential oil is characterized by comprising the following steps of:
collecting a near infrared spectrum chart and a Raman spectrum chart of a lavender essential oil sample to be detected;
Fusing the near infrared spectrogram and the Raman spectrogram to obtain a fused spectrogram;
preprocessing the fusion spectrogram to obtain a preprocessed fusion spectrogram;
constructing a quantitative analysis model using the construction method of any one of claims 1 to 7;
Substituting the fusion spectrogram of the lavender essential oil sample to be detected after pretreatment into a constructed quantitative analysis model, and predicting the linalool, linalyl acetate and lavender acetate content of the lavender essential oil sample to be detected.
9. The method of claim 8, wherein the method further comprises: collecting a near infrared spectrum and a Raman spectrum of a lavender essential oil sample to be detected, performing baseline correction and vector normalization processing on the near infrared spectrum and the Raman spectrum to obtain a preprocessed near infrared spectrum and a preprocessed Raman spectrum, and then fusing the preprocessed near infrared spectrum and the preprocessed Raman spectrum;
Or the method further comprises: after collecting a near infrared spectrum of a lavender essential oil sample, carrying out baseline correction and vector normalization treatment on the near infrared spectrum to obtain a preprocessed near infrared spectrum; after collecting a Raman spectrum of a lavender essential oil sample, carrying out baseline correction and vector normalization processing on the Raman spectrum to obtain a pretreated Raman spectrum; and then fusing the preprocessed near infrared spectrum and the preprocessed Raman spectrum.
10. The method of claim 9, wherein the fused spectral map is first derivative preprocessed to obtain the first derivative map of the fused spectrum.
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