CN112595691A - Establishment method and quantitative analysis method of lavender essential oil characteristic component quantitative analysis model based on near-infrared Raman spectrum fusion - Google Patents
Establishment method and quantitative analysis method of lavender essential oil characteristic component quantitative analysis model based on near-infrared Raman spectrum fusion Download PDFInfo
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- 244000178870 Lavandula angustifolia Species 0.000 title claims abstract description 126
- 235000010663 Lavandula angustifolia Nutrition 0.000 title claims abstract description 126
- 239000001102 lavandula vera Substances 0.000 title claims abstract description 125
- 235000018219 lavender Nutrition 0.000 title claims abstract description 125
- 239000000341 volatile oil Substances 0.000 title claims abstract description 104
- 238000000034 method Methods 0.000 title claims abstract description 74
- 238000001228 spectrum Methods 0.000 title claims abstract description 74
- 238000004445 quantitative analysis Methods 0.000 title claims abstract description 47
- 230000004927 fusion Effects 0.000 title claims abstract description 31
- 238000002095 near-infrared Raman spectroscopy Methods 0.000 title claims abstract description 9
- 238000001069 Raman spectroscopy Methods 0.000 claims abstract description 68
- 238000012937 correction Methods 0.000 claims abstract description 55
- 238000001237 Raman spectrum Methods 0.000 claims abstract description 36
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 28
- 238000010606 normalization Methods 0.000 claims abstract description 26
- 238000012545 processing Methods 0.000 claims abstract description 17
- 238000004458 analytical method Methods 0.000 claims abstract description 15
- 238000004817 gas chromatography Methods 0.000 claims abstract description 13
- UWKAYLJWKGQEPM-LBPRGKRZSA-N linalyl acetate Chemical compound CC(C)=CCC[C@](C)(C=C)OC(C)=O UWKAYLJWKGQEPM-LBPRGKRZSA-N 0.000 claims description 42
- CDOSHBSSFJOMGT-UHFFFAOYSA-N linalool Chemical compound CC(C)=CCCC(C)(O)C=C CDOSHBSSFJOMGT-UHFFFAOYSA-N 0.000 claims description 40
- 238000007781 pre-processing Methods 0.000 claims description 22
- UWKAYLJWKGQEPM-UHFFFAOYSA-N linalool acetate Natural products CC(C)=CCCC(C)(C=C)OC(C)=O UWKAYLJWKGQEPM-UHFFFAOYSA-N 0.000 claims description 21
- 238000012795 verification Methods 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
- 229930007744 linalool Natural products 0.000 claims description 20
- QTBSBXVTEAMEQO-UHFFFAOYSA-M Acetate Chemical compound CC([O-])=O QTBSBXVTEAMEQO-UHFFFAOYSA-M 0.000 claims description 16
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- 230000003287 optical effect Effects 0.000 claims description 5
- 239000012159 carrier gas Substances 0.000 claims description 4
- CZVXBFUKBZRMKR-UHFFFAOYSA-N lavandulol Chemical compound CC(C)=CCC(CO)C(C)=C CZVXBFUKBZRMKR-UHFFFAOYSA-N 0.000 claims description 4
- 238000012360 testing method Methods 0.000 claims description 3
- CZVXBFUKBZRMKR-JTQLQIEISA-N (R)-lavandulol Natural products CC(C)=CC[C@@H](CO)C(C)=C CZVXBFUKBZRMKR-JTQLQIEISA-N 0.000 claims description 2
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- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 1
- 241000207923 Lamiaceae Species 0.000 description 1
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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, and the method comprises the following specific steps: (1) collecting a lavender essential oil sample; (2) obtaining the characteristic and representative component percentage content of the lavender essential oil sample according to gas chromatography in national standard; (3) collecting near-infrared light and Raman spectrograms of the lavender essential oil sample, and performing baseline correction and vector normalization processing on the measured near-infrared light and Raman spectrograms; (4) and for the near infrared spectrum and the Raman spectrum, the spectrum is fused in a mode of parallel connection of the spectrums, and the same coordinate is shared. (5) Establishing a partial least square quantitative correction model; (6) and measuring the lavender essential oil sample by adopting the established quantitative analysis model. The quantitative quality analysis of the lavender essential oil by using the method is simple and convenient to operate, accurate, time-saving and efficient.
Description
Technical Field
The invention relates to the technical field of measuring the content of characteristic components of lavender essential oil, in particular to a method for establishing a quantitative analysis model of characteristic components 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 effects of tranquilizing, relieving depression, improving sleep, eliminating stagnation, and dispelling pathogenic wind. The lavender essential oil is a complex mixture composed of various aromatic compounds of different types, wherein the proportion of different compounds directly influences the quality of the lavender essential oil, the content of characteristic components in the lavender essential oil is determined by using a gas chromatography in the national standard of the lavender essential oil, and the national standard GB/T12653-2008 of the lavender (essential) oil is that the qualified range of the content (w/%) of representative and characteristic components is as follows: linalool 20-43%; 25 to 47 percent of linalyl acetate; lavender acetate ≦ 8%.
At present, methods for measuring chemical components of 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 large-batch rapid quantitative detection.
In view of the above, the present invention is particularly proposed.
Disclosure of Invention
The invention aims to provide a method for establishing a quantitative analysis model of characteristic components of lavender essential oil.
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 determine the content of various characteristic components of lavender essential oil.
In order to achieve the above purpose of the present invention, the following technical solutions are adopted:
in a first aspect, the invention provides a method for establishing a quantitative analysis model of characteristic components of lavender essential oil, which comprises the following steps:
collecting a near infrared spectrogram and a Raman spectrogram of a lavender essential oil sample;
fusing the near-infrared spectrogram and the Raman spectrogram to obtain a fused spectrogram;
preprocessing the fused spectrogram to obtain a preprocessed fused spectrogram;
establishing a quantitative analysis model among linalool, linalyl acetate and lavandulol acetate contents and a near-infrared Raman fusion spectrum of the 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 includes: after acquiring a near infrared spectrogram and a Raman spectrogram of a lavender essential oil sample, performing baseline correction and vector normalization treatment on the near infrared spectrogram and the Raman spectrogram to obtain a pretreated near infrared spectrogram and a pretreated Raman spectrogram, and then fusing the pretreated near infrared spectrogram and the Raman spectrogram;
or, the establishing method further includes: after the near-infrared spectrogram of the lavender essential oil sample is collected, carrying out baseline correction and vector normalization processing on the near-infrared spectrogram to obtain a preprocessed near-infrared spectrogram; after collecting the Raman spectrogram of the lavender essential oil sample, carrying out baseline correction and vector normalization processing on the Raman spectrogram to obtain a preprocessed Raman spectrogram; and then fusing the preprocessed near-infrared spectrogram and the preprocessed Raman spectrogram.
Furthermore, the lavender essential oil sample is from Yili area of Xinjiang, all samples are divided into a calibration set sample and a verification set sample, the calibration set sample is used for establishing a calibration model, and the verification set sample is used for verifying the model.
Furthermore, the near infrared spectrogram is acquired by using a transmission mode, a quartz cuvette with an optical path of 1mm is selected, the ambient temperature is 22 ℃, and the scanning range is 4000cm-1～6600cm-1Resolution of 8cm-1Scanning for 32 times, firstly scanning the background, then measuring the lavender essential oil samples under the same experimental conditions, measuring each sample for 3 times in parallel, and taking an average value;
preferably, the Raman spectrogram is acquired by using a laser with a wavelength of 532nm, the laser power is 100mW, the ambient temperature is 22 ℃, and the spectral data is acquired by measuring for 3s under a 50 x objective lens after absorbing the lavender essential oil by using a glass capillary tube, wherein the spectral acquisition range is 600cm-1～3200cm-1Each sample was tested three times, averaged, and the average spectrum was taken as the analysis spectrum.
Further, fusing the near infrared spectrum and the raman spectrum includes:
the spectrum is fused in a mode of parallel connection of the spectrums, the same coordinate is shared, the abscissa of the fused spectrogram is a spectrum channel, and the ordinate of the fused spectrogram is the summation intensity value of the parallel spectrums.
Further, the preprocessing method for fusing the spectrogram comprises first derivative, multivariate scattering correction or standard normal transformation;
preferably, the fused spectrogram is subjected to first derivative preprocessing to obtain a first derivative of the fused spectrogram.
Further, the evaluation and testing of the quantitative analysis model comprises:
determining the coefficient R between the predicted value and the reference value of the correction set2The correction set cross validation mean square error RMSECV and the correction standard deviation RMSEC are used as model evaluation indexes to evaluate the rationality of the model;
and measuring the performance of the model by using the verification set samples to predict standard deviation RESEP and prediction set measurement coefficient Rp2To measure the predictive performance of the model.
Further, the measuring method of the content of linalool, linalyl acetate and lavender acetate in the lavender essential oil sample is gas chromatography in GB/T12653-2008 lavender (essential) oil;
preferably, the chromatographic conditions of the gas chromatography method comprise:
a chromatographic column: RTX-50MS quartz capillary column;
temperature programming: keeping at 50 deg.C for 5min, and keeping at 2 deg.C/min-1Heating to 100 deg.C, 3 deg.C, min-1Heating to 150 deg.C, 8 deg.C, min-1Heating to 250 deg.C and maintaining for 5 min;
carrier gas flow rate 1.16 mL/min-1And the pressure is 65.2 KPa.
In a second aspect, the invention provides a quantitative analysis method for characteristic components of lavender essential oil, which is characterized by collecting a near-infrared spectrogram and a Raman spectrogram 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 fused spectrogram to obtain a preprocessed fused spectrogram;
constructing a quantitative analysis model by using the establishing method;
and substituting the preprocessed fusion spectrogram of the lavender essential oil sample to be detected into the constructed quantitative analysis model to predict the content of linalool, linalyl acetate and lavender ester in the lavender essential oil sample to be detected.
Further, the quantitative analysis method further comprises: after acquiring a near-infrared spectrogram and a Raman spectrogram of a lavender essential oil sample, performing baseline correction and vector normalization processing on the near-infrared spectrogram and the Raman spectrogram to obtain a preprocessed near-infrared spectrogram and a preprocessed Raman spectrogram, and then fusing the preprocessed near-infrared spectrogram and the preprocessed Raman spectrogram;
alternatively, the quantitative analysis method further comprises: after a near-infrared spectrogram of a lavender essential oil sample is collected, performing baseline correction and vector normalization processing on the near-infrared spectrogram to obtain a preprocessed near-infrared spectrogram; after collecting the Raman spectrogram of the lavender essential oil sample, carrying out baseline correction and vector normalization processing on the Raman spectrogram to obtain a preprocessed Raman spectrogram; and then fusing the preprocessed near-infrared spectrogram and the preprocessed Raman spectrogram.
Preferably, the fused spectrogram is subjected to first derivative preprocessing to obtain a first derivative of the fused spectrogram.
The establishment method and the quantitative analysis method of the lavender essential oil characteristic component quantitative analysis model provided by the invention at least have 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 large batch in actual production can be solved, and the near infrared spectrum and Raman spectrum have strong complementarity, so that the obtained fusion spectrum information is comprehensive, and the chemical information of the lavender essential oil can be embodied comprehensively.
The method of the invention does not need sample treatment, and compared with the traditional gas chromatography and gas chromatography mass spectrometry, the method can obtain the analysis result within a few minutes, and the analysis efficiency is greatly improved. The method has the advantages of good robustness, high fitting degree and high prediction precision, can quickly determine the content of main components in the lavender essential oil, and provides a quick, accurate, simple, convenient and feasible measurement method which is easy to popularize and apply for quick 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 used in the embodiments or the prior art descriptions will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a schematic flow chart of a quantitative analysis method for characteristic components of lavender essential oil according to the present invention;
FIG. 2 is a near infrared spectrogram and a vector normalized near infrared spectrogram of lavender essential oil (a: the near infrared spectrogram, b: the vector normalized spectrogram);
FIG. 3 is a Raman spectrogram and a vector-normalized Raman spectrogram of lavender essential oil (a: Raman spectrogram, b: spectrogram after vector normalization);
FIG. 4 is a fused spectrum of near infrared Raman parallel addition after vector normalization according to an embodiment;
FIG. 5 shows a spectrum obtained by applying three different preprocessing methods to the fused spectrum in the embodiment (a: first derivative, lst Der, b: multivariate scattering correction, MSC, c: normal transformation, SNV);
FIG. 6 is a correlation graph between the predicted fused spectrogram value and the GC-MS measured value of a calibration set sample of the PLS model of the example (a: linalool, b: linalyl acetate, c: lavender acetate);
FIG. 7 is a graph showing the correlation between the predicted results and GC-MS measurements for the validated set of lavender essential oil samples of the examples (a: linalool, b: linalyl acetate, c: lavender acetate).
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
At present, methods for measuring chemical components of lavender essential oil mainly include a gas chromatography and a gas chromatography-mass spectrometry combined method, but the methods are time-consuming and difficult to realize large-batch rapid quantitative detection, and near infrared spectroscopy and raman spectroscopy analysis technologies have the advantages of high analysis speed, short analysis time, non-destructiveness, no chemical pollution, no need of complex sample treatment process, low cost, easiness in realization of online detection and the like, are particularly suitable for large-batch sample test, are widely applied to quality detection in the fields of agriculture, food industry, chemical industry, pharmaceutical industry and the like, and become a modern technology for rapid analysis.
Near Infrared (NIR) obtains characteristic information of combined frequency and frequency multiplication of the hydrogen-containing group vibration of the detected organic molecules, and the NIR spectrum overlapping degree is high. Raman spectrum (RAMAN) obtains the Raman scattering intensity of the detected organic matter, and the spectrum overlapping degree is low. Unlike near infrared spectroscopy, both polar and nonpolar molecules can produce raman spectra, and the obtained information has strong complementarity with the near infrared spectroscopy.
The method comprises the steps of respectively measuring the near-infrared absorption spectrum and the Raman scattering spectrum of the lavender essential oil, and performing spectrum data accumulation and fusion on the near-infrared spectrum and the Raman spectrum after certain data preprocessing and spectrum band screening. Compared with a single Raman spectrum and a near infrared spectrum, the data subjected to spectrum fusion can more comprehensively reflect the chemical information of the lavender essential oil, so that the method for determining the contents of various characteristic components of the lavender essential oil based on the NIR and RAMAN spectrum fusion technologies is established.
The near infrared spectroscopy and the Raman spectroscopy are both rapid analysis methods, can realize on-site and on-line analysis, can finish the measurement of various characteristic components of the lavender essential oil only by completing the acquisition and measurement of the near infrared spectrum and the Raman spectrum of a sample to be measured within a few minutes, and do not need complex pretreatment processes and chemical reagents in the measurement process.
As shown in fig. 1, the invention provides a method (quantitative analysis method) for measuring contents of various characteristic components (the characteristic components mainly refer to linalool, linalyl acetate and lavender acetate) of lavender essential oil based on near-infrared and raman spectrum fusion technologies, which comprises the following steps:
The source of the lavender essential oil sample is not limited, and is preferably from the Yili area of Xinjiang.
In a preferred embodiment, the near infrared spectral acquisition uses transmission mode, a quartz cuvette with an optical path of 1mm is selected, the ambient temperature is 22 ℃, and the scanning range is 4000cm-1～6600cm-1Resolution of 8cm-1The number of scanning accumulation is 32, background scanning is firstly carried out, and then the background scanning is carried out under the same experimental conditionsLavender essential oil samples were measured, each sample was measured in parallel 3 times, and the average value was taken.
In a preferred embodiment, the Raman spectroscopy uses a 532nm laser with a laser power of 100mW and an ambient temperature of 22 deg.C, and after adsorbing the lavender essential oil of step 1 with a 0.3mm × 10mm glass capillary, the spectral data is obtained by measuring 3s under a 50 × objective lens, and the spectral collection range is 600cm-1～3200cm-1Each sample was tested three times, averaged, and the average spectrum was taken as the analysis spectrum.
And 3, preprocessing the near-infrared spectrogram and the Raman spectrogram obtained in the step 2.
In a preferred embodiment, baseline correction and vector normalization processing are carried out on the near-infrared spectrogram and the Raman spectrogram, background interference is eliminated, and the ordinate values of the near-infrared spectrogram and the Raman spectrogram are in the same order of magnitude, so that the near-infrared spectrogram and the Raman spectrogram after lavender essential oil sample pretreatment are obtained.
After baseline correction is carried out on the near infrared spectrum and the Raman spectrum, the ordinate of the near infrared spectrogram is an absorption intensity value, the ordinate of the Raman spectrum is a Raman scattering intensity value, the difference between the absorption intensity value and the Raman scattering intensity value is large, and vector normalization processing is carried out to enable the ordinate of the near infrared spectrum and the ordinate of the Raman spectrum to be in the same order of magnitude in order to eliminate the inconsistency of the ordinate of the near infrared spectrum and the Raman spectrum.
The specific baseline correction and vector normalization processing can be performed in a conventional manner.
It should be noted that the preprocessing may be performed after both the near-infrared spectrogram and the raman spectrogram are obtained, or may be performed after separate spectrograms are obtained (the near-infrared spectrogram is preprocessed after the near-infrared spectrogram is obtained, and the raman spectrogram is preprocessed after the raman spectrogram is obtained).
And 4, spectrum fusion: and (3) fusing the near infrared spectrum and the Raman spectrum pretreated in the step (3).
In a preferred embodiment, the spectra are fused in a parallel manner, sharing the same coordinates. The abscissa of the fused spectrum is a spectrum channel, and the ordinate of the fused spectrum is a summation intensity value of the parallel spectra.
The mode of parallel spectrum refers to the accumulation of near infrared and Raman spectrum data.
Parallel spectra refer to near infrared and raman spectra.
The near infrared spectrum range is as follows: 4000cm-1～6600cm-1Raman spectrum ranging from 600cm-1～ 3200cm-1. All from low wavenumber to high wavenumber, every 4cm-1Taking a data point, wherein the number of data channels of the near infrared spectrum and the Raman spectrum are 650, and the weight ratio of the near infrared spectrum to the Raman spectrum in fusion is 1: and 1, adding the data on the same channel by the near infrared spectrum and the Raman spectrum by adopting a parallel fusion method to obtain new fusion data, wherein the abscissa is the spectrum channel 1-650, and the ordinate is the data addition value of the near infrared spectrum and the Raman spectrum, and the fused spectrum data contains richer chemical component characteristic information.
Step 5, fused spectrum pretreatment: and (4) preprocessing the fused spectrogram obtained in the step (4).
The pre-treatment method used First derivative (lst Der), Multivariate Scatter Correction (MSC), Standard normal transformation (SNV) for screening.
The optimized fused spectrum preprocessing method obtained through the model evaluation indexes is a first derivative method.
In a preferred embodiment, the fused spectrogram is subjected to first derivative preprocessing to obtain a first derivative chart of the fused spectrum of the lavender essential oil sample.
The method for establishing the optimized quantitative analysis model comprises the following steps:
step a, collecting a representative lavender essential oil sample.
The lavender essential oil samples were all from the Yili area of Xinjiang.
And dividing all samples 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 selecting a correction set sample by uniformly distributing the content of linalool, linalyl acetate and lavender acetate, establishing a quantitative analysis correction model, and carrying out external verification on the model by taking the rest samples as a verification set.
And b, collecting a near infrared spectrogram and a Raman spectrogram 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, the near infrared spectral acquisition uses transmission mode, a quartz cuvette with an optical path of 1mm is selected, the ambient temperature is 22 ℃, and the scanning range is 4000cm-1～6600cm-1Resolution of 8cm-1And performing background scanning for 32 times, measuring lavender essential oil samples under the same experimental conditions, measuring each sample for 3 times in parallel, and averaging.
In a preferred embodiment, the Raman spectroscopy uses a 532nm laser with a laser power of 100mW and an ambient temperature of 22 deg.C, and after adsorbing the lavender essential oil of step 1 with a 0.3mm × 10mm glass capillary, the spectral data is obtained by measuring 3s under a 50 × objective lens, and the spectral collection range is 600cm-1～3200cm-1Each sample was tested three times, averaged, and the average spectrum was taken as the analysis spectrum.
And c, performing baseline correction and vector normalization pretreatment on the near-infrared spectrogram and the Raman spectrogram of all the determined samples to eliminate background interference and inconsistency of the near-infrared spectrum intensity and the Raman spectrum intensity, wherein the baseline correction and the vector normalization pretreatment are the same as those in the step 3 and are not repeated herein.
And d, fusing the preprocessed near-infrared spectrogram and the preprocessed Raman spectrogram, fusing spectrums in a spectrum parallel mode, sharing the same coordinate, wherein the abscissa of the fused spectrum is a spectrum channel, and the ordinate of the fused spectrum is the summation intensity value of the parallel spectrums, and the fusion is the same as that in the step 4, and is not repeated.
And e, preprocessing the fused spectrum data of the lavender essential oil sample.
The preprocessing method adopts First derivative (lst Der), Multiple Scattering Correction (MSC), and Standard normal transformation (SNV) to perform screening, and the obtained fusion spectrum optimization preprocessing method is a First derivative method.
And f, establishing a quantitative analysis correction model among the linalool, linalyl acetate and lavender acetate percentage content (w/%) and the fusion spectrum of the lavender essential oil sample by adopting a Partial Least Squares (PLS).
And (3) correlating the fusion spectrum of the correction set sample with the content of the characteristic components of the lavender essential oil by a partial least square method, and respectively establishing quantitative analysis models of linalool, linalyl acetate and lavender ester acetate. And obtaining the correlation between the predicted values of the percentage contents of the linalool, the linalyl acetate and the lavender acetate in the calibration set and the verification set samples and the control value.
In a preferred embodiment, the content of linalool, linalyl acetate, lavender acetate was determined by gas chromatography in "GB/T12653-2008 lavender (essential) oil chinese", all samples of lavender essential oil as a control.
The gas chromatography measurement adopts an RTX-50MS quartz capillary column (30m multiplied by 0.25mm) chromatographic column; temperature programming: keeping at 50 deg.C for 5min, and keeping at 2 deg.C/min-1Heating to 100 deg.C, 3 deg.C, min-1Heating to 150 deg.C, 8 deg.C, min-1Heating to 250 deg.C and maintaining for 5 min; flow rate of carrier gas (99.999% He) 1.16 mL/min-1And the pressure is 65.2 KPa.
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 measuring the coefficient R between the predicted value and the reference value of the correction set2Correction set cross validation mean square error (Root M)ean Square Error of Cross-Validation, RMSECV), and corrected standard deviation (RMSEC) as model evaluation indexes, R2Closer to 1, smaller RMSECV and RMSEC, the more reasonable the correction model is established.
The model is checked and evaluated by an external verification method, and the Prediction performance of the model is measured by a verification set sample to predict the standard deviation (RESET) and the Prediction set determination coefficient Rp2And measuring the prediction performance of the model, and obtaining the optimized quantitative analysis model after the model is conformed to the prediction performance.
The process of the model construction method can be summarized as follows:
selecting a sufficient number of representative lavender essential oil samples to form a correction set, firstly measuring the content of characteristic components of the samples by using the current national standard method as a comparison value, then measuring the near infrared spectrum and the Raman spectrum of the samples, and performing parallel accumulation and fusion on the near infrared spectrum data and the Raman spectrum data after baseline correction and vector normalization processing of the spectrum data respectively. And establishing a quantitative analysis model between the fused spectrum information and the characteristic component content of the lavender essential oil by adopting a Partial Least Squares (PLS) chemometrics algorithm. The method comprises the steps of forming a verification set by a group of samples with known lavender essential oil characteristic component content, measuring near infrared and Raman spectrums of the verification set samples, performing baseline correction and vector normalization processing, connecting data in parallel to form a verification set fusion spectrum, and calculating the corresponding lavender essential oil characteristic component content by using an established model so as to verify and evaluate the established model. If the validation set is within an acceptable range of variation, 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 are prepared according to known methods or are directly commercially available, unless otherwise specified.
Examples
1. The lavender essential oil samples were collected, all the samples were 100 lavender essential oil samples from the yili area of Xinjiang, and all the samples were divided into 70 calibration set samples, 30 verification set samples, the calibration set samples were used for establishing a calibration model, the verification set samples were used for verifying a model, and the characteristic component content distributions of the final calibration set and verification set samples are shown in Table 1 below.
TABLE 1 Lavender essential oil characteristic component percentage distribution
2. Instrument for measuring the position of a moving object
Fourier transform near-infrared spectrometer: VERTEX 70, BRUKER; laser Raman spectrometer: LabRAM HR Evolution, HORBIA corporation; gas chromatograph: agilent Technologies, 5890.
3. Spectrum acquisition and pre-processing
3.1 near Infrared Spectroscopy Collection and Pre-treatment
Using transmission mode, selecting quartz cuvette with optical path of 1mm, ambient temperature of 22 deg.C, scanning range of 4000cm-1～6600cm-1Resolution of 8cm-1And performing scanning accumulation for 32 times, performing background scanning, measuring lavender essential oil samples under the same experimental conditions, performing parallel measurement for 3 times on each sample, and performing averaging, baseline correction and vector normalization pretreatment, near infrared spectrum and vector normalization treatment to obtain a graph shown in figure 2.
3.2 Raman Spectroscopy Collection and pretreatment
Adopting a 532nm laser with laser power of 100mW and ambient temperature of 22 deg.C, adsorbing the lavender essential oil in step 1 with 0.3mm × 10mm glass capillary, measuring for 3s under 50 × objective lens to obtain spectral data, wherein the spectral collection range is 600cm-1～3200cm-1Each sample was tested three times, averaged, and the averaged spectrum was used as the analysis spectrum, pre-processed for baseline correction and vector normalization, and processed for raman spectroscopy and vector normalization as shown in fig. 3.
4. Spectral fusion
Fusing the preprocessed near infrared spectrum and the preprocessed Raman spectrum, wherein the spectrum fusion is the parallel accumulation fusion of the near infrared spectrum data and the Raman spectrum data, and the near infrared spectrum range is as follows: 4000cm-1～6600cm-1Raman spectrum ranging from 600cm-1～3200cm-1. All from low wavenumber to high wavenumber, every 4cm-1Taking a data point, wherein the number of data channels of the near infrared spectrum and the Raman spectrum are 650, and the weight ratio of the near infrared spectrum to the Raman spectrum in fusion is 1: and 1, adding the data on the same channel by the near infrared spectrum and the Raman spectrum by adopting a parallel fusion method to obtain new fusion data, wherein the abscissa is the spectrum channel 1-650, and the ordinate is the data addition value of the near infrared spectrum and the Raman spectrum, so that the fused spectrum data obviously contains richer chemical component characteristic information. The fused spectrum is shown in FIG. 4.
5. Establishment of correction model
5.1 measurement of characteristic value content of lavender essential oil sample
The contents (w/%) of linalool, linalyl acetate and lavender acetate in all lavender essential oil samples were determined by gas chromatography in "GB/T12653-2008 lavender (essential) oil of china" as control values.
Chromatographic conditions chromatographic column: RTX-50MS quartz capillary column (30 m.times.0.25 mm); temperature programmed: keeping at 50 deg.C for 5min, and keeping at 2 deg.C/min-1Heating to 100 deg.C, 3 deg.C, min-1Heating to 150 deg.C, 8 deg.C, min-1Heating to 250 deg.C and maintaining for 5 min; flow rate of carrier gas (99.999% He) 1.16 mL/min-1And the pressure is 65.2 KPa.
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: first derivative (First Derivatives, lst Der), Multivariate Scatter Correction (MSC), Standard normal transformation (SNV), three fused spectra after pretreatment are shown in fig. 5, and finally the First derivative is preferably the optimized fused spectrum pretreatment method (see table 2).
Establishing a quantitative correction model between linalool, linalyl acetate, percentage content of linalyl acetate (w/%) and fusion spectrum of the lavender essential oil sample by adopting Partial Least Squares (PLS), and measuring between a predicted value and a reference value of a correction setConstant coefficient R2The correction set Cross Validation Mean Square Error (RMSECV) and the correction standard deviation (RMSECV) are used as model evaluation indexes, and R is the standard deviation of the Cross Validation of the correction set2Closer to 1, smaller RMSECV and RMSEC, the more reasonable the correction model is established. External validation is performed using validation set samples to measure model performance by measuring the Root Mean Square Error of Prediction (RESEP), predicting set measurement coefficients Rp2Measurement of the predictive Performance, Rp, of the model2Closer to 1, the smaller the RMSEP, indicating more accurate model predictions (see table 2). The correlation graphs of the percentage content predicted values of linalool, linalyl acetate and lavender acetate in the calibration set and the verification set samples and the comparison value measured by the gas chromatography-mass spectrometry are respectively shown in the attached figures 6 and 7. By the method, the analysis results of the percentage contents (w/%) of linalool, linalyl acetate and lavender acetate in the lavender essential oil sample can be quickly obtained. The established NIR-RAMAN-PLS fused spectrum quantitative analysis model is good in robustness, fitting degree and high in prediction precision, the content of main components in the lavender essential oil can be rapidly determined, and a simple, convenient and rapid measurement method is provided for rapid quantitative analysis of the lavender essential oil.
TABLE 2 Lavender essential oil characteristic component quantitative correction model and verification result
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and such modifications and substitutions do not depart from the spirit and scope of the present invention as defined by the appended claims.
Claims (10)
1. The method for establishing the quantitative analysis model of the characteristic components of the lavender essential oil is characterized by comprising the following steps of:
collecting a near infrared spectrogram and a Raman spectrogram of a lavender essential oil sample;
fusing the near-infrared spectrogram and the Raman spectrogram to obtain a fused spectrogram;
preprocessing the fused spectrogram to obtain a preprocessed fused spectrogram;
establishing a quantitative analysis model among linalool, linalyl acetate and lavandulol acetate contents and a near-infrared Raman fusion spectrum of the 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.
2. The method of claim 1, further comprising: after acquiring a near-infrared spectrogram and a Raman spectrogram of a lavender essential oil sample, performing baseline correction and vector normalization processing on the near-infrared spectrogram and the Raman spectrogram to obtain a preprocessed near-infrared spectrogram and a preprocessed Raman spectrogram, and then fusing the preprocessed near-infrared spectrogram and the preprocessed Raman spectrogram;
or, the establishing method further includes: after a near-infrared spectrogram of a lavender essential oil sample is collected, carrying out baseline correction and vector normalization processing on the near-infrared spectrogram to obtain a preprocessed near-infrared spectrogram; after collecting the Raman spectrogram of the lavender essential oil sample, carrying out baseline correction and vector normalization processing on the Raman spectrogram to obtain a preprocessed Raman spectrogram; and then fusing the preprocessed near-infrared spectrogram and the preprocessed Raman spectrogram.
3. The establishing method according to claim 1 or 2, wherein the lavender essential oil sample is from Yili area of Xinjiang, the sample is divided into a calibration set sample and a verification set sample, the calibration set sample is used for establishing a calibration model, and the verification set sample is used for verifying the model.
4. The method of construction according to claim 1 or 2, wherein the near infrared spectrogram collection is performed in transmission mode by selecting a quartz cuvette with an optical length of 1mm, an ambient temperature of 22 ℃, and a scanning range of 4000cm-1～6600cm-1Resolution of 8cm-1Scanning for 32 times, firstly scanning the background, measuring lavender essential oil samples under the same experimental conditions, measuring each sample for 3 times in parallel, and taking an average value;
preferably, the Raman spectrogram is acquired by using a laser with a wavelength of 532nm, the laser power is 100mW, the ambient temperature is 22 ℃, and the spectral data is acquired by measuring for 3s under a 50 x objective lens after absorbing the lavender essential oil by using a glass capillary tube, wherein the spectral acquisition range is 600cm-1～3200cm-1Each sample was tested three times, averaged, and the average spectrum was taken as the analysis spectrum.
5. The method of building of claim 1 or 2, wherein fusing the near infrared spectrum and the raman spectrum comprises:
the spectrum is fused in a mode of parallel connection of the spectrums, the same coordinate is shared, the abscissa of the fused spectrogram is a spectrum channel, and the ordinate of the fused spectrogram is the summation intensity value of the parallel spectrums.
6. The method of establishing according to claim 1 or 2, wherein the preprocessing method of fusing the spectrogram comprises first derivative, multivariate scatter correction or standard normal transformation;
preferably, the fused spectrogram is subjected to first derivative preprocessing to obtain a first derivative of the fused spectrogram.
7. The method of claim 3, wherein evaluating and testing the quantitative analysis model comprises:
determining the coefficient R between the predicted value and the reference value of the correction set2Correction set cross validation mean square error RMSECV, correction standard deviation RMSEC asModel evaluation indexes, which are used for evaluating the rationality of the model;
and measuring the performance of the model by using the verification set samples to predict standard deviation RESEP and prediction set measurement coefficient Rp2To measure the predictive performance of the model.
8. The establishing method according to claim 1 or 2, characterized in that the measuring method of the linalool, linalyl acetate and lavender acetate content of the lavender essential oil sample is gas chromatography in GB/T12653-2008 lavender (essential) oil;
preferably, the chromatographic conditions of the gas chromatography method comprise:
a chromatographic column: RTX-50MS quartz capillary column;
temperature programming: keeping at 50 deg.C for 5min, and keeping at 2 deg.C/min-1Heating to 100 deg.C, 3 deg.C, min-1Heating to 150 deg.C, 8 deg.C, min-1Heating to 250 deg.C and maintaining for 5 min;
carrier gas flow rate 1.16 mL/min-1And the pressure is 65.2 KPa.
9. A quantitative analysis method for characteristic components of lavender essential oil is characterized by comprising the following steps:
collecting a near infrared spectrogram and a Raman spectrogram 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 fused spectrogram to obtain a preprocessed fused spectrogram;
constructing a quantitative analysis model using the building method of any one of claims 1 to 8;
and substituting the preprocessed fusion spectrogram of the lavender essential oil sample to be detected into the constructed quantitative analysis model to predict the content of linalool, linalyl acetate and lavender ester acetate in the lavender essential oil sample to be detected.
10. The method of claim 9, further comprising: after acquiring a near-infrared spectrogram and a Raman spectrogram of a lavender essential oil sample to be detected, performing baseline correction and vector normalization processing on the near-infrared spectrogram and the Raman spectrogram to obtain a preprocessed near-infrared spectrogram and a preprocessed Raman spectrogram, and then fusing the preprocessed near-infrared spectrogram and the preprocessed Raman spectrogram;
alternatively, the method further comprises: after a near-infrared spectrogram of a lavender essential oil sample is collected, carrying out baseline correction and vector normalization processing on the near-infrared spectrogram to obtain a preprocessed near-infrared spectrogram; after collecting the Raman spectrogram of the lavender essential oil sample, carrying out baseline correction and vector normalization processing on the Raman spectrogram to obtain a preprocessed Raman spectrogram; then, fusing the preprocessed near-infrared spectrogram and the preprocessed Raman spectrogram;
preferably, the fused spectrogram is subjected to first derivative preprocessing to obtain a first derivative of the fused spectrogram.
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