CN109632702A - A kind of detection method of honeysuckle content - Google Patents
A kind of detection method of honeysuckle content Download PDFInfo
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- CN109632702A CN109632702A CN201910058799.2A CN201910058799A CN109632702A CN 109632702 A CN109632702 A CN 109632702A CN 201910058799 A CN201910058799 A CN 201910058799A CN 109632702 A CN109632702 A CN 109632702A
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- honeysuckle
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- 238000001514 detection method Methods 0.000 title claims abstract description 30
- 241000205585 Aquilegia canadensis Species 0.000 title claims abstract 15
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 35
- 238000013528 artificial neural network Methods 0.000 claims description 9
- 238000001228 spectrum Methods 0.000 claims description 9
- 230000004913 activation Effects 0.000 claims description 7
- PCHJSUWPFVWCPO-UHFFFAOYSA-N gold Chemical compound [Au] PCHJSUWPFVWCPO-UHFFFAOYSA-N 0.000 claims description 7
- 229910052737 gold Inorganic materials 0.000 claims description 7
- 239000010931 gold Substances 0.000 claims description 7
- 238000007873 sieving Methods 0.000 claims description 6
- 230000003595 spectral effect Effects 0.000 claims description 4
- 238000012549 training Methods 0.000 claims description 4
- 230000005540 biological transmission Effects 0.000 claims description 3
- 239000000843 powder Substances 0.000 claims description 2
- 238000012545 processing Methods 0.000 claims description 2
- 238000000034 method Methods 0.000 abstract description 16
- 239000003814 drug Substances 0.000 abstract description 7
- 239000000463 material Substances 0.000 abstract description 5
- 239000003153 chemical reaction reagent Substances 0.000 abstract description 4
- 241000628997 Flos Species 0.000 abstract description 3
- 241001570521 Lonicera periclymenum Species 0.000 description 86
- 239000000523 sample Substances 0.000 description 36
- 239000000203 mixture Substances 0.000 description 8
- BQCADISMDOOEFD-UHFFFAOYSA-N Silver Chemical compound [Ag] BQCADISMDOOEFD-UHFFFAOYSA-N 0.000 description 4
- 229910052709 silver Inorganic materials 0.000 description 4
- 239000004332 silver Substances 0.000 description 4
- CWVRJTMFETXNAD-FWCWNIRPSA-N 3-O-Caffeoylquinic acid Natural products O[C@H]1[C@@H](O)C[C@@](O)(C(O)=O)C[C@H]1OC(=O)\C=C\C1=CC=C(O)C(O)=C1 CWVRJTMFETXNAD-FWCWNIRPSA-N 0.000 description 3
- PZIRUHCJZBGLDY-UHFFFAOYSA-N Caffeoylquinic acid Natural products CC(CCC(=O)C(C)C1C(=O)CC2C3CC(O)C4CC(O)CCC4(C)C3CCC12C)C(=O)O PZIRUHCJZBGLDY-UHFFFAOYSA-N 0.000 description 3
- CWVRJTMFETXNAD-KLZCAUPSSA-N Neochlorogenin-saeure Natural products O[C@H]1C[C@@](O)(C[C@@H](OC(=O)C=Cc2ccc(O)c(O)c2)[C@@H]1O)C(=O)O CWVRJTMFETXNAD-KLZCAUPSSA-N 0.000 description 3
- CWVRJTMFETXNAD-JUHZACGLSA-N chlorogenic acid Chemical compound O[C@@H]1[C@H](O)C[C@@](O)(C(O)=O)C[C@H]1OC(=O)\C=C\C1=CC=C(O)C(O)=C1 CWVRJTMFETXNAD-JUHZACGLSA-N 0.000 description 3
- 229940074393 chlorogenic acid Drugs 0.000 description 3
- FFQSDFBBSXGVKF-KHSQJDLVSA-N chlorogenic acid Natural products O[C@@H]1C[C@](O)(C[C@@H](CC(=O)C=Cc2ccc(O)c(O)c2)[C@@H]1O)C(=O)O FFQSDFBBSXGVKF-KHSQJDLVSA-N 0.000 description 3
- 235000001368 chlorogenic acid Nutrition 0.000 description 3
- BMRSEYFENKXDIS-KLZCAUPSSA-N cis-3-O-p-coumaroylquinic acid Natural products O[C@H]1C[C@@](O)(C[C@@H](OC(=O)C=Cc2ccc(O)cc2)[C@@H]1O)C(=O)O BMRSEYFENKXDIS-KLZCAUPSSA-N 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- 241001128140 Reseda Species 0.000 description 2
- 235000009508 confectionery Nutrition 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 241000208828 Caprifoliaceae Species 0.000 description 1
- 241001170080 Lonicera hypoglauca Species 0.000 description 1
- 241000888295 Lonicera subspicata Species 0.000 description 1
- 238000004587 chromatography analysis Methods 0.000 description 1
- 229930194605 dipsacoside Natural products 0.000 description 1
- 238000012850 discrimination method Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 239000006101 laboratory sample Substances 0.000 description 1
- 210000004218 nerve net Anatomy 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 239000001397 quillaja saponaria molina bark Substances 0.000 description 1
- 238000011897 real-time detection Methods 0.000 description 1
- 229930182490 saponin Natural products 0.000 description 1
- 150000007949 saponins Chemical class 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
Classifications
-
- 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
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- 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
-
- 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
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- 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
- G01N2021/3595—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using FTIR
Abstract
The present invention provides a kind of detection methods of honeysuckle content, belong to Chinese medicine study field.The detection method for the honeysuckle content based on near-infrared spectrum technique that the present invention provides a kind of, the present invention is compared with identification teacher's identification method and chromatographic process, minute can be greatly shortened, identification experience independent of identification teacher, a large amount of reagents are not needed, prepare without complicated sample early period, saves a large amount of man power and material.Therefore, the present invention can provide a kind of new method for specification traditional Chinese medicine honeysuckle market and guarantee pharmaceutical factory quality of Flos Lonicerae reliability.
Description
Technical field
The invention belongs to Chinese medicine study technical field more particularly to a kind of detection methods of honeysuckle content.
Background technique
Honeysuckle title comes from Compendium of Material Medica, also known as " honeysuckle ", and tcm clinical practice is used as medicine with honeysuckle dry flower, is had
Clearing heat and detoxicating effect.Honeysuckle flower is caprifoliaceae plant, originates in southern region of China, largeflower-like honeysuckle flower, lonicera hypoglauca miq, China extensively
Southern honeysuckle or fulvoushair honeysuckle flower are classified as Honeysuckle flower.Honeysuckle, Honeysuckle flower form are similar, are visually difficult to distinguish.However,
The two but has different medical values." Chinese Pharmacopoeia " (2015 editions) are using chlorogenic acid, the sweet content of reseda as honeysuckle matter
The evaluation criterion of amount；Using chlorogenic acid, largeflower-like honeysuckle flower saponin second, dipsacoside as the evaluation criterion of Honeysuckle flower quality.
In recent years, the market demand of honeysuckle constantly increases, and promotes the market price of honeysuckle constantly soaring, this also results in some mountains
The appearance for phenomena such as honeysuckle flower pretends to be honeysuckle or Honeysuckle flower to mix honeysuckle, has seriously affected the interests of consumer.
In order to identify to honeysuckle and Honeysuckle flower melange, currently used main method is using traditional artificial mirror
Main matter component content in other and chromatography determination sample.However artificial identification result is relied on and is passed through with the identification of identification teacher
It tests, subjectivity is strong, and not can be carried out large batch of inspection；Chromatographic process can provide the exact composition content letter of measured object
Breath, however need first to carry out solid-state sample traditional Chinese medicine extraction, and process is tedious for chromatographic process early-stage preparations, needs additional
Reagent auxiliary, more demanding to operator, at high cost, the testing time is long, is not able to satisfy the needs of real-time detection.Be not suitable for city
The field test of field buying and the high-volume of pharmaceutical factory supplied materials are examined.Because of a kind of convenient and efficient efficient honeysuckle of the invention, mountain silver
Flower melange discrimination method is particularly important.
Summary of the invention
In view of this, the purpose of the present invention is to provide a kind of detection methods of honeysuckle content.Inspection provided by the invention
Survey method can fast implement honeysuckle, in Honeysuckle flower melange honeysuckle content measurement.
In order to achieve the above-mentioned object of the invention, the present invention the following technical schemes are provided:
The present invention provides a kind of detection methods of honeysuckle content, comprising the following steps:
Honeysuckle is mixed with Honeysuckle flower, obtains sample set；
The near infrared spectrum for acquiring the sample set, proof gold honeysuckle flower and pure Honeysuckle flower obtains near infrared spectrum collection；
The characteristic wave bands for selecting the near infrared spectrum collection establish detection model, the feature in conjunction with BP- neural network
The wavelength of wave band is 4200~4381cm-1, 4489~4867cm-1With 5350~6900cm-1；
Honeysuckle sample to be measured is analyzed according to detection model, detects the content of honeysuckle in honeysuckle sample.
Preferably, the mass gradient ratio of Honeysuckle flower is 10%, 15%, 20%, 25%, 30% in the sample set,
35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85% and 90%.
Preferably, the honeysuckle also carries out crushing before mixing with Honeysuckle flower and sieving processing, the aperture of the sieving are small
In 0.25 μm.
Preferably, diffusing transmission type collection near infrared spectrum, the Fourier are used by Fourier near infrared spectrometer
The spectral resolution of near infrared spectrometer is 4~8cm-1, automatically scanning number 32~64 times, take for each sample repeated acquisition 3 times
Average, spectrum wave-number range is 4000~10000cm-1。
Preferably, the BP- neural network includes input layer, hidden layer and output layer, the choosing of the node in hidden layer
It selects according to formulaIt calculates, wherein n is input layer number, and m is output layer number of nodes, and a is [1,10] section
A variable, the activation primitive of the hidden layer is tansig, and the activation primitive of the output layer is purelin, network
Training function is traingdm.
The present invention provides a kind of detection methods of honeysuckle content, comprising the following steps: by honeysuckle and Honeysuckle flower into
Row mixing, obtains sample set；The near infrared spectrum for acquiring the sample set, proof gold honeysuckle flower and pure Honeysuckle flower, obtains near infrared light
Spectrum collection；The characteristic wave bands for selecting the near infrared spectrum collection establish detection model, the characteristic wave bands in conjunction with BP- neural network
Wavelength be 4200~4381cm-1, 4489~4867cm-1With 5350~6900cm-1；According to detection model to gold and silver to be measured
Style is originally analyzed, and the content of honeysuckle in honeysuckle sample is detected.The present invention provides one kind to be based near infrared spectrum skill
The detection method of the honeysuckle content of art, the present invention can greatly shorten measurement compared with identification teacher's identification method and chromatographic process
Time does not need a large amount of reagents independent of the identification experience of identification teacher, prepares without complicated sample early period, saves big
The man power and material of amount.Therefore, the present invention can be specification traditional Chinese medicine honeysuckle market and guarantee pharmaceutical factory quality of Flos Lonicerae reliability
A kind of new method is provided.
Detailed description of the invention
Fig. 1 is the flow chart of the detection method of 1 honeysuckle content of the embodiment of the present invention；
Fig. 2 is the original atlas of near infrared spectra of honeysuckle；
Fig. 3 is that Honeysuckle flower is averaged atlas of near infrared spectra；
Fig. 4 is sample sets atlas of near infrared spectra；
Fig. 5 is modeling effect picture；
Fig. 6 is the verification result figure of model.
Specific embodiment
The present invention provides a kind of detection methods of honeysuckle content, comprising the following steps:
Honeysuckle is mixed with Honeysuckle flower, obtains sample set；
The near infrared spectrum for acquiring the sample set, proof gold honeysuckle flower and pure Honeysuckle flower obtains near infrared spectrum collection；
The characteristic wave bands for selecting the near infrared spectrum collection establish detection model, the feature in conjunction with BP- neural network
The wavelength of wave band is 4200~4381cm-1, 4489~4867cm-1With 5350~6900cm-1；
Honeysuckle sample to be measured is analyzed according to detection model, detects the content of honeysuckle in honeysuckle sample.
The present invention mixes honeysuckle with Honeysuckle flower, obtains sample set.In the present invention, mountain silver in the sample set
Colored mass gradient ratio is preferably 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%,
65%, 70%, 75%, 80%, 85% and 90%.
The present invention does not have special restriction to the source of the honeysuckle and Honeysuckle flower, using known to those skilled in the art
Commercial goods, it is specific as 1 batch of Henan pan honeysuckle flower and Hunan produce 3 batches of Honeysuckle flower.The present invention is to described
Hybrid mode does not have special restriction, using hybrid mode well known to those skilled in the art.
In the present invention, the honeysuckle further preferably carries out crushing before mixing with Honeysuckle flower and sieving is handled, the sieving
Aperture be preferably smaller than 0.25 μm.The present invention does not have special restriction to the concrete mode of the crushing, using art technology
Technical solution known to personnel.
After obtaining sample set, the present invention acquires the near infrared spectrum of the sample set, proof gold honeysuckle flower and pure Honeysuckle flower, obtains
Near infrared spectrum collection.In the present invention, it is preferred to pass through the diffusing transmission type collection near infrared spectrum of Fourier near infrared spectrometer,
The spectral resolution of the Fourier near infrared spectrometer is preferably 4~8cm-1, automatically scanning number is preferably 32~64 times, often
A sample repeats to be averaged for preferred acquisition 3 times, and spectrum wave-number range is preferably 4000~10000cm-1。
In the present invention, the near infrared spectrum collection that the Fourier near infrared spectrometer obtains preferably takes what is automatically generated to put down
Equal input of the spectrum as model.In the present invention, the data for the near infrared spectrum that the Fourier near infrared spectrometer obtains
Processing software preferably uses matlab, version R2017a.
After obtaining near infrared spectrum collection, the present invention selects the characteristic wave bands of the near infrared spectrum collection, in conjunction with BP- nerve net
Network, establishes detection model, and the wavelength of the characteristic wave bands is 4200~4381cm-1, 4489~4867cm-1With 5350~
6900cm-1.In the present invention, the BP- neural network preferably includes input layer, hidden layer and output layer, the hidden layer section
The selection of points is preferably according to formulaIt calculates, wherein n is input layer number, and m is output layer number of nodes, a
For a variable in [1,10] section, the activation primitive of the hidden layer is preferably tansig, the activation primitive of the output layer
The training function of preferably purelin, network are preferably traingdm.
After obtaining detection model, the present invention analyzes honeysuckle sample to be measured according to detection model, detects gold and silver
The content of honeysuckle in style sheet.In the present invention, it is preferred to carry out near infrared spectra collection to the honeysuckle sample, will obtain
Near infrared spectrum spectrogram characteristic wave bands data imported into the detection model after, can be obtained in honeysuckle sample golden
The content of honeysuckle flower.
A kind of detection method of honeysuckle content provided by the invention is described in detail below with reference to embodiment, but
It is that they cannot be interpreted as limiting the scope of the present invention.
Embodiment 1
Fig. 1 is the flow chart of the detection method of 1 honeysuckle content of embodiment, collection, spectra collection including sample, feature
Model and model application are established in the selection of wave band.
1. the collection of sample: laboratory sample is that 1 batch of Henan pan honeysuckle flower and Hunan produce 3 batches of Honeysuckle flower, crush,
No. 4 sieves are crossed, are respectively 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45% according to honeysuckle and Honeysuckle flower accounting,
50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, it is mixed, takes each 5 grams of every part of melange, there are
To 51 parts of sample sets.Sample sets powder is respectively placed in sample carrier, is gently beaten to close tight.
2. sample set near infrared spectra collection: being produced using near infrared spectra collection instrument using Thermo Fisher company
Fourier near infrared spectrometer, software use Result software, 4000~10000cm of spectral scanning range-1, each spectra collection
It scans 32 times altogether, resolution ratio 8cm-1, automatic collection 3 times, take input of the averaged spectrum automatically generated as model.Data processing
Software uses matlab, version R2017a.The collected original atlas of near infrared spectra of honeysuckle is as shown in Figure 2；Honeysuckle flower is flat
Equal atlas of near infrared spectra is as shown in Figure 3；Sample sets atlas of near infrared spectra is as shown in Figure 4.
3. the foundation of calibration model: according to the near infrared spectrum of the honeysuckle, Honeysuckle flower and sample sets, in conjunction with reseda
Sweet, chlorogenic acid characteristic wave bands section selects characteristic wave bands, identifies model in conjunction with BP- neural network.To each mixed proportion
Sample chooses foundation of 34 parts of melanges as calibration set for model according to the ratio of 2:1, and remaining 17 parts of melanges, which are used as, to be tested
Card collection is used for the verifying of model.The near infrared spectrum of measured object is often related to its chemical composition content, is based on this principle, this hair
4200~4381cm of bright selection-1, 4489~4867cm-1, 5350~6900cm-1It is characterized wave band and establishes and identify model.It establishes
BP- neural network, including input layer, hidden layer and output layer.Wherein the selection of node in hidden layer is according to formulaWherein n is input layer number, and m is output layer number of nodes, and a is a variable in [1,10] section.Hidden layer
Activation primitive with output layer is respectively tansig, and purelin, the training function of network is traingdm.Model effect such as Fig. 5
It is shown.
4. the verifying of model
The model of foundation is verified using the near infrared spectrum of 16 melange samples of selection as verifying collection.It examines
The predictive ability of model.Choose 4200~4381cm-1, 4489~4867cm-1, 5350~6900cm-1For 16 melange samples
Characteristic spectrum, the input as established calibration model.Verification result is shown in as shown in Figure 6.It sets predicted value and true value is inclined
Difference is correct for prediction less than 5%, and verifying collection predictablity rate is 82.3%.
The results show can be used for unknown honeysuckle and Honeysuckle flower mixing sample mixing ratio by means of the present invention
Identify.And the present invention can greatly shorten minute, independent of identification compared with identification teacher's identification method and chromatographic process
The identification experience of teacher, does not need a large amount of reagents, prepares without complicated sample early period, saves a large amount of man power and material.Cause
This, the present invention can provide a kind of new method for specification traditional Chinese medicine honeysuckle market and guarantee pharmaceutical factory quality of Flos Lonicerae reliability.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered
It is considered as protection scope of the present invention.
Claims (5)
1. a kind of detection method of honeysuckle content, which comprises the following steps:
Honeysuckle is mixed with Honeysuckle flower, obtains sample set；
The near infrared spectrum for acquiring the sample set, proof gold honeysuckle flower and pure Honeysuckle flower obtains near infrared spectrum collection；
The characteristic wave bands for selecting the near infrared spectrum collection establish detection model, the characteristic wave bands in conjunction with BP- neural network
Wavelength be 4200~4381cm-1, 4489~4867cm-1With 5350~6900cm-1；
Honeysuckle sample to be measured is analyzed according to detection model, detects the content of honeysuckle in honeysuckle sample.
2. detection method according to claim 1, which is characterized in that the mass gradient ratio of Honeysuckle flower in the sample set
It is 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%,
85% and 90%.
3. detection method according to claim 1, which is characterized in that the honeysuckle also carries out powder before mixing with Honeysuckle flower
Broken and sieving processing, the aperture of the sieving is less than 0.25 μm.
4. detection method according to claim 1, which is characterized in that use diffusing transmission by Fourier near infrared spectrometer
Type collection near infrared spectrum, the spectral resolution of the Fourier near infrared spectrometer are 4~8cm-1, automatically scanning number 32
It~64 times, is averaged for each sample repeated acquisition 3 times, spectrum wave-number range is 4000~10000cm-1。
5. detection method according to claim 1, which is characterized in that the BP neural network includes input layer, hidden layer
And output layer, the selection of the node in hidden layer is according to formulaIt calculates, wherein n is input layer number, m
For output layer number of nodes, a is a variable in [1,10] section, and the activation primitive of the hidden layer is tansig, the output
The activation primitive of layer is purelin, and the training function of network is traingdm.
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| CN201910058799.2A CN109632702A (en) | 2019-01-22 | 2019-01-22 | A kind of detection method of honeysuckle content |
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| CN201910058799.2A CN109632702A (en) | 2019-01-22 | 2019-01-22 | A kind of detection method of honeysuckle content |
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Family
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| CN114199812A (en) * | 2021-12-28 | 2022-03-18 | 南通联亚药业有限公司 | Method for detecting memantine hydrochloride in memantine hydrochloride sustained-release preparation |
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Cited By (2)
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| CN114199812A (en) * | 2021-12-28 | 2022-03-18 | 南通联亚药业有限公司 | Method for detecting memantine hydrochloride in memantine hydrochloride sustained-release preparation |
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