CN106442385A - Method of spectrum detection of anthocyanidin content in mulberry - Google Patents
Method of spectrum detection of anthocyanidin content in mulberry Download PDFInfo
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- CN106442385A CN106442385A CN201610872230.6A CN201610872230A CN106442385A CN 106442385 A CN106442385 A CN 106442385A CN 201610872230 A CN201610872230 A CN 201610872230A CN 106442385 A CN106442385 A CN 106442385A
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- mulberries
- anthocyanidin content
- mulberry
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- 235000008708 Morus alba Nutrition 0.000 title claims abstract description 60
- 229930014669 anthocyanidin Natural products 0.000 title claims abstract description 42
- 235000008758 anthocyanidins Nutrition 0.000 title claims abstract description 42
- 238000001228 spectrum Methods 0.000 title claims abstract description 21
- 238000001514 detection method Methods 0.000 title claims abstract description 19
- 238000000034 method Methods 0.000 title claims abstract description 19
- 240000000249 Morus alba Species 0.000 title claims abstract description 13
- 150000001452 anthocyanidin derivatives Chemical class 0.000 title claims abstract 14
- 230000003595 spectral effect Effects 0.000 claims abstract description 13
- 238000009614 chemical analysis method Methods 0.000 claims abstract description 4
- 241000218231 Moraceae Species 0.000 claims description 47
- 238000012417 linear regression Methods 0.000 claims description 7
- 238000000605 extraction Methods 0.000 claims description 2
- 238000002310 reflectometry Methods 0.000 claims description 2
- 150000001453 anthocyanidins Chemical class 0.000 description 28
- 240000004385 Centaurea cyanus Species 0.000 description 3
- 235000005940 Centaurea cyanus Nutrition 0.000 description 3
- 108010023832 Florigen Proteins 0.000 description 3
- OKKJLVBELUTLKV-UHFFFAOYSA-N Methanol Chemical compound OC OKKJLVBELUTLKV-UHFFFAOYSA-N 0.000 description 3
- 238000002835 absorbance Methods 0.000 description 3
- 230000001261 florigenic effect Effects 0.000 description 3
- 235000021022 fresh fruits Nutrition 0.000 description 3
- 229930182478 glucoside Natural products 0.000 description 3
- 239000007788 liquid Substances 0.000 description 3
- QTBSBXVTEAMEQO-UHFFFAOYSA-N Acetic acid Chemical compound CC(O)=O QTBSBXVTEAMEQO-UHFFFAOYSA-N 0.000 description 2
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 2
- WCUXLLCKKVVCTQ-UHFFFAOYSA-M Potassium chloride Chemical compound [Cl-].[K+] WCUXLLCKKVVCTQ-UHFFFAOYSA-M 0.000 description 2
- 239000007853 buffer solution Substances 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 229930002877 anthocyanin Natural products 0.000 description 1
- 235000010208 anthocyanin Nutrition 0.000 description 1
- 239000004410 anthocyanin Substances 0.000 description 1
- 150000004636 anthocyanins Chemical class 0.000 description 1
- 230000001093 anti-cancer Effects 0.000 description 1
- 230000003110 anti-inflammatory effect Effects 0.000 description 1
- 230000008033 biological extinction Effects 0.000 description 1
- 238000005119 centrifugation Methods 0.000 description 1
- 238000010790 dilution Methods 0.000 description 1
- 239000012895 dilution Substances 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000036039 immunity Effects 0.000 description 1
- 239000007791 liquid phase Substances 0.000 description 1
- 229910052757 nitrogen Inorganic materials 0.000 description 1
- 238000009659 non-destructive testing Methods 0.000 description 1
- 235000011164 potassium chloride Nutrition 0.000 description 1
- 239000001103 potassium chloride Substances 0.000 description 1
- 238000010298 pulverizing process Methods 0.000 description 1
- 150000003254 radicals Chemical class 0.000 description 1
- 239000007974 sodium acetate buffer Substances 0.000 description 1
- 238000004611 spectroscopical analysis Methods 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 239000006228 supernatant Substances 0.000 description 1
Classifications
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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
- G01N21/17—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
- G01N21/3563—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light for analysing solids; Preparation of samples therefor
-
- 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
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- Physics & Mathematics (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The invention discloses a method of spectrum detection of the anthocyanidin content in mulberry. The method comprises the steps of a, collecting a hyperspectral image of a mulberry sample; b, adopting a chemical analysis method to measure a reference value of the anthocyanidin content in the mulberry sample; c, extracting information of characteristic wavelengths in the hyperspectral image of the mulberry sample and using the extracted information as an input, using the reference value of the anthocyanidin content in the mulberry sample as an output, and establishing a model; d, collecting a spectral image under the characteristic wavelengths in the mulberry sample to be detected, and using the model established in the step c to measure the anthocyanidin content in the mulberry to be detected. In addition, the wavelengths in the step c are 985 nm and 1389 nm respectively. The method of spectrum detection of the anthocyanidin content in mulberry realizes fast and nondestructive detection of the anthocyanidin content in the mulberry.
Description
Technical field
The present invention relates to fruit quality detection field, more particularly, to a kind of spectral method of detection of mulberries anthocyanidin content.
Background technology
Mulberries contain abundant anthocyanidin.Anthocyanidin has non-oxidizability, can remove internal free radical, have raising
The effects such as immunity, anti-inflammatory, anticancer, be conducive to health.Therefore anthocyanidin content be mulberries quality important indicator it
One.
Existing anthocyanidin content detection method is mainly chemical analysis method at present, and such as pH shows poor method, high-efficient liquid phase color
Spectrometry etc..The accuracy of these methods detection is higher, but being required for pulverizing sample is examined extracting anthocyanidin therein again
Survey, testing cost height, labor intensive and time, be only suitable for inspecting by random samples on a small quantity it is difficult to daily use is to mulberries Quality Detection and quality
In classification.
Content of the invention
The present invention proposes a kind of mulberries anthocyanidin content spectral method of detection it is achieved that containing to the anthocyanidin of mulberries fresh fruit
Amount Fast nondestructive evaluation.
A kind of spectral method of detection of mulberries anthocyanidin content is it is characterised in that comprise the following steps：
A, by the high spectrum image of Hyperspectral imager receiving of mulberry seed sample；It is 920nm that the present invention takes wavelength
The data of 1660nm is used for subsequent analysis；
B, with chemical analysis method measure mulberries sample anthocyanidin content as reference value；
In c, the described mulberries high spectrum image of extraction, the information of characteristic wavelength is input, with the anthocyanidin content of mulberries sample
Reference value is output, sets up multiple linear regression model；
D, the spectrum picture gathering under mulberries characteristic wavelength to be measured；
E, according to the spectrum picture under the characteristic wavelength of step d, calculated using the multiple linear regression model that step c is set up
The anthocyanidin content of mulberries to be measured.
Characteristic wavelength wherein in step c is 985nm and 1389nm.The multiple linear regression mould set up by mulberries sample
Type is as follows：
Y=6.6491-17.1623 × X985+19.5293×X1389
Wherein, Y is mulberries anthocyanidin content (unit：Mg/g), with Cy-3-G as equivalent；
XnMean value for the reflectivity under n nm for each pixel of mulberries in high spectrum image.
Mulberries anthocyanidin content spectral method of detection of the present invention can realize the quick of the anthocyanidin content to mulberries fresh fruit
Non-Destructive Testing.
Brief description
Fig. 1 is the flow chart of the spectral method of detection of mulberries anthocyanidin content；
Fig. 2 is the apparatus structure schematic diagram of receiving of mulberry seed high spectrum image；
Fig. 3 is the averaged spectrum curve map of mulberries sample；
Fig. 4 is the comparison diagram of mulberries anthocyanidin content reference value and predicted value.
Specific embodiment
Now the spectral method of detection of mulberries anthocyanidin content is elaborated as follows：
(1) 40 parts of the different fresh mulberries of anthocyanidin content are taken.Every part of sample is gathered by Hyperspectral imager
The high spectrum image of 920nm-1660nm, comprises the following steps that：
A, mulberries are placed on mobile platform, adjustment light source is just to mulberries；
B, by computer software manipulate mobile platform move, EO-1 hyperion camera line scanning obtain whole mulberries height
Spectrum picture.
(2) show that poor method obtains the anthocyanidin content reference value of 40 parts of mulberries samples using pH, concrete operation step is as follows：
A, by every part of mulberries sample with liquid nitrogen frost after pulverize；
B, accurately weigh 0.40g sample, (volume ratio consists of with 8ml extract：MeOH/H2O/AcOH, 425:75:
2.5) at 4 DEG C, lucifuge is extracted 24 hours.3000rpm centrifugation takes supernatant in 10 minutes；
C, addition 9ml potassium chloride buffer solution (0.025M, pH=1.0) in 1ml extract；Add in 1ml extract
9ml sodium-acetate buffer (0.4M, pH=4.5)；
D, lucifuge measure absorbance under 510nm and 700nm for two groups of cushioning liquid respectively after stablizing 1 hour, according to such as
Lower formula calculates the Anthocyanin content (corn flower florigen -3- glucoside equivalent) of every gram of mulberries fresh fruit：
In formula：A is absorbance, A=(A510nm pH1.0-A700nm pH1.0)-(A510nm pH4.5-A700nm pH4.5)；A510nm pH1.0、
A700nm pH1.0、A510nm pH4.5、A700nm pH4.5Absorbance at different wavelengths respectively after the different pH buffer solutions of addition.
ε is the extinction coefficient of corn flower florigen -3- glucoside, ε=26,900L mol-1·cm-1；
L is light path, L=1cm；
MW is the molecular weight of corn flower florigen -3- glucoside, MW=449.2g mol-1；
DF is dilution gfactor, DF=10；
V is extracting liquid volume, V=0.008L；
W is mulberries example weight, W=0.40g.
(3) adopt matlab software programming, extract every in the mulberries sample high spectrum image of collection from step (1) respectively
The spectral reflectance of individual sample is used for inputting, and shows that the anthocyanidin content reference value that poor method obtains is defeated using pH with step (2)
Go out, characteristic wavelength is extracted using successive projection algorithm (SPA), obtaining characteristic wavelength referring to Fig. 3 is 985nm and 1389nm.And build
Vertical multiple linear regression (MLR) model, model is：
Y=6.6491-17.1623 × X985+19.5293×X1389
Wherein, Y is mulberries anthocyanidin content (unit：Mg/g), with Cy-3-G as equivalent；
XnMean value for the spectral reflectance under n nm for each pixel of mulberries in high spectrum image.
(4) take 20 parts of mulberries to be measured, high spectrum image is gathered by Hyperspectral imager, extract the spectrum of characteristic wavelength
Data, calculates anthocyanidin content predicted value according to the model of step (3).
In order to verify model accuracy, the method using step (2) measures mulberries anthocyanidin content reference value to be measured, with mould
Type prediction anthocyanidin content is compared, and the results are shown in Table 1 and Fig. 4.Statistical analysis shows the coefficient of determination (r of forecast model2) be
0.9383, the root-mean-square error (RMSEP) of predicted value is 0.1527mg/g.
The anthocyanidin predicted value of table 1 mulberries to be measured and reference value
It can be seen that multiple linear regression model of the present invention has preferable prediction effect, can effectively distinguish mulberries to be measured
Anthocyanidin content height, thus carrying out Quality Detection and classification.
Claims (3)
1. a kind of spectral method of detection of mulberries anthocyanidin content is it is characterised in that comprise the following steps：
A, by the high spectrum image of Hyperspectral imager receiving of mulberry seed sample；
B, using chemical analysis method measure mulberries sample total anthocyanidin content as reference value；
In c, the described high spectrum image of extraction, the data of characteristic wavelength is input, and the anthocyanidin content reference value with mulberries sample is
Output, sets up multiple linear regression model；
D, the spectrum picture gathering under mulberries characteristic wavelength to be measured；
E, according to the spectrum picture under the characteristic wavelength of step d, calculate the anthocyanidin of mulberries to be measured using the model that step c is set up
Content.
2. the spectral method of detection of mulberries anthocyanidin content as claimed in claim 1 is it is characterised in that feature in step c
Wavelength is 985nm and 1389nm.
3. the spectral method of detection of mulberries anthocyanidin content as claimed in claim 2 is it is characterised in that built by mulberries sample
Vertical multiple linear regression model is as follows：
Y=6.6491-17.1623 × X985+19.5293×X1389
Wherein, Y is mulberries anthocyanidin content, unit：Mg/g, with Cy-3-G as equivalent；
XnMean value for the reflectivity under n nm for each pixel of mulberries in high spectrum image.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201610872230.6A CN106442385A (en) | 2016-09-30 | 2016-09-30 | Method of spectrum detection of anthocyanidin content in mulberry |
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| CN201610872230.6A CN106442385A (en) | 2016-09-30 | 2016-09-30 | Method of spectrum detection of anthocyanidin content in mulberry |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111795932A (en) * | 2020-06-15 | 2020-10-20 | 杭州电子科技大学 | Hyperspectrum-based nondestructive testing method for sugar acidity of waxberry fruits |
| CN112304921A (en) * | 2020-10-23 | 2021-02-02 | 中国计量大学 | Method for detecting anthocyanin in mulberry based on Raman spectrum technology |
| CN116306984A (en) * | 2023-05-16 | 2023-06-23 | 北京市农林科学院信息技术研究中心 | Training and detecting method and device for detecting fresh She Huase glycoside of purple crops |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111795932A (en) * | 2020-06-15 | 2020-10-20 | 杭州电子科技大学 | Hyperspectrum-based nondestructive testing method for sugar acidity of waxberry fruits |
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| CN112304921B (en) * | 2020-10-23 | 2022-05-03 | 中国计量大学 | Method for detecting anthocyanin in mulberry based on Raman spectrum technology |
| CN116306984A (en) * | 2023-05-16 | 2023-06-23 | 北京市农林科学院信息技术研究中心 | Training and detecting method and device for detecting fresh She Huase glycoside of purple crops |
| CN116306984B (en) * | 2023-05-16 | 2023-09-12 | 北京市农林科学院信息技术研究中心 | Training and detecting method and device for detecting fresh She Huase glycoside of purple crops |
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