CN106442357A - Spectrum detection method for antioxidant activity of mulberries - Google Patents
Spectrum detection method for antioxidant activity of mulberries Download PDFInfo
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- CN106442357A CN106442357A CN201610873376.2A CN201610873376A CN106442357A CN 106442357 A CN106442357 A CN 106442357A CN 201610873376 A CN201610873376 A CN 201610873376A CN 106442357 A CN106442357 A CN 106442357A
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- China
- Prior art keywords
- antioxidant activity
- fructus mori
- mulberries
- sample
- reference value
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- 230000003078 antioxidant effect Effects 0.000 title claims abstract description 40
- 238000001228 spectrum Methods 0.000 title claims abstract description 21
- 238000001514 detection method Methods 0.000 title claims abstract description 17
- 235000008708 Morus alba Nutrition 0.000 title claims abstract description 12
- 241000218231 Moraceae Species 0.000 title abstract 7
- 238000000034 method Methods 0.000 claims abstract description 21
- 240000000249 Morus alba Species 0.000 claims abstract description 5
- 238000009614 chemical analysis method Methods 0.000 claims abstract description 4
- CIWBSHSKHKDKBQ-JLAZNSOCSA-N Ascorbic acid Chemical compound OC[C@H](O)[C@H]1OC(=O)C(O)=C1O CIWBSHSKHKDKBQ-JLAZNSOCSA-N 0.000 claims description 10
- 230000003595 spectral effect Effects 0.000 claims description 10
- 238000012417 linear regression Methods 0.000 claims description 7
- ZZZCUOFIHGPKAK-UHFFFAOYSA-N D-erythro-ascorbic acid Natural products OCC1OC(=O)C(O)=C1O ZZZCUOFIHGPKAK-UHFFFAOYSA-N 0.000 claims description 5
- 229930003268 Vitamin C Natural products 0.000 claims description 5
- 235000019154 vitamin C Nutrition 0.000 claims description 5
- 239000011718 vitamin C Substances 0.000 claims description 5
- 238000002310 reflectometry Methods 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 2
- 238000009659 non-destructive testing Methods 0.000 abstract description 2
- OKKJLVBELUTLKV-UHFFFAOYSA-N Methanol Chemical compound OC OKKJLVBELUTLKV-UHFFFAOYSA-N 0.000 description 6
- HHEAADYXPMHMCT-UHFFFAOYSA-N dpph Chemical compound [O-][N+](=O)C1=CC([N+](=O)[O-])=CC([N+]([O-])=O)=C1[N]N(C=1C=CC=CC=1)C1=CC=CC=C1 HHEAADYXPMHMCT-UHFFFAOYSA-N 0.000 description 4
- 235000021022 fresh fruits Nutrition 0.000 description 3
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 2
- 238000002835 absorbance Methods 0.000 description 2
- 229930014669 anthocyanidin Natural products 0.000 description 2
- 150000001452 anthocyanidin derivatives Chemical class 0.000 description 2
- 235000008758 anthocyanidins Nutrition 0.000 description 2
- 230000003064 anti-oxidating effect Effects 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 239000000284 extract Substances 0.000 description 2
- 239000007788 liquid Substances 0.000 description 2
- 150000001299 aldehydes Chemical class 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000001093 anti-cancer Effects 0.000 description 1
- 230000003110 anti-inflammatory effect Effects 0.000 description 1
- OHDRQQURAXLVGJ-HLVWOLMTSA-N azane;(2e)-3-ethyl-2-[(e)-(3-ethyl-6-sulfo-1,3-benzothiazol-2-ylidene)hydrazinylidene]-1,3-benzothiazole-6-sulfonic acid Chemical compound [NH4+].[NH4+].S/1C2=CC(S([O-])(=O)=O)=CC=C2N(CC)C\1=N/N=C1/SC2=CC(S([O-])(=O)=O)=CC=C2N1CC OHDRQQURAXLVGJ-HLVWOLMTSA-N 0.000 description 1
- 238000005119 centrifugation Methods 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
- 229930003935 flavonoid Natural products 0.000 description 1
- 150000002215 flavonoids Chemical class 0.000 description 1
- 235000017173 flavonoids Nutrition 0.000 description 1
- 238000002376 fluorescence recovery after photobleaching Methods 0.000 description 1
- 230000036039 immunity Effects 0.000 description 1
- 239000010977 jade Substances 0.000 description 1
- 239000000401 methanolic extract Substances 0.000 description 1
- 229910052757 nitrogen Inorganic materials 0.000 description 1
- 150000003254 radicals Chemical class 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 239000006228 supernatant Substances 0.000 description 1
- 229930003231 vitamin Natural products 0.000 description 1
- 235000013343 vitamin Nutrition 0.000 description 1
- 239000011782 vitamin Substances 0.000 description 1
- 229940088594 vitamin Drugs 0.000 description 1
- 150000003722 vitamin derivatives Chemical class 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
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/28—Investigating the spectrum
- G01J3/2823—Imaging spectrometer
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
- G01J3/28—Investigating the spectrum
- G01J3/2823—Imaging spectrometer
- G01J2003/2826—Multispectral imaging, e.g. filter imaging
Abstract
The invention discloses a spectrum detection method for antioxidant activity of mulberries. The method comprises the following steps: a, collecting a hyperspectral image of a mulberry sample; b, measuring a reference value of the antioxidant activity of mulberries by adopting a chemical analysis method; c, extracting characteristic wavelength information in the hyperspectral image of the mulberry as input, taking the reference value of the antioxidant activity of mulberries as output, and establishing a model; and d, collecting a spectrum image under characteristic wavelengths of to-be-detected mulberries, and calculating the antioxidant activity of the to-be-detected mulberries by utilizing the model established in the step c, wherein the characteristic wavelengths in the step c is 941nm, 1460nm and 1659nm. According to the method disclosed by the invention, rapid nondestructive testing of the antioxidant activity of the mulberries is realized.
Description
Technical field
The present invention relates to fruit quality detection field, more particularly to a kind of spectral method of detection of Fructus Mori antioxidant activity.
Background technology
Fructus Mori contain abundant flavonoid and aldehydes matter, such as anthocyanidin, vitamin etc., live with higher antioxidation
Property, can remove internal free radical, the effects such as with enhance immunity, anti-inflammatory, anticancer, be conducive to health.Therefore
Antioxidant activity can be used as one of index for evaluating Fructus Mori quality.
Existing antioxidant activity detection method is mainly chemical analysis method, such as DPPH method, ABTS method, FRAP method at present
Deng.The degree of accuracy of these method detections is higher, but is required for crushing sample to be detected again, testing cost height, labor intensive
And the time, it is only suitable for a small amount of sampling observation, it is difficult in daily use to Fructus Mori Quality Detection and quality grading.
Content of the invention
The present invention proposes a kind of Fructus Mori antioxidant activity spectral method of detection, it is achieved that the antioxidation of Fructus Mori fresh fruit is lived
Property Fast nondestructive evaluation.
The pass uncut jade detection method of a kind of Fructus Mori antioxidant activity, it is characterised in that comprise the following steps：
A, by the high spectrum image of Hyperspectral imager receiving of mulberry seed sample；The present invention takes wavelength for 920nm
The data of 1660nm are used for subsequent analysis；
B, with chemical analysis method determine Fructus Mori sample antioxidant activity as reference value；
In c, the extraction Fructus Mori high spectrum image, the information of characteristic wavelength is input, with the antioxidant activity of Fructus Mori sample
Reference value is output, sets up multiple linear regression model；
D, the spectrum picture for gathering under Fructus Mori 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 antioxidant activity of Fructus Mori to be measured.
Characteristic wavelength wherein in step c is 941nm, 1460nm and 1659nm.The polynary line that is set up by Fructus Mori sample
Property regression model is as follows：
Y=14.6875-16.3270 × X941+163.1246×X1460-83.3823×X1659
Wherein, Y is Fructus Mori antioxidant activity (unit：μm ol/g), with vitamin C as equivalent；
XnMeansigma methodss for the reflectivity of each pixel under n nm of Fructus Mori in high spectrum image.
Fructus Mori antioxidant activity spectral method of detection of the present invention can achieve quick to the antioxidant activity of Fructus Mori fresh fruit
Non-Destructive Testing.
Description of the drawings
Fig. 1 is the flow chart of the spectral method of detection of Fructus Mori antioxidant activity；
Fig. 2 is the apparatus structure schematic diagram of receiving of mulberry seed high spectrum image；
Fig. 3 is the averaged spectrum curve chart of Fructus Mori sample；
Fig. 4 is the comparison diagram of Fructus Mori antioxidant activity reference value and predictive value.
Specific embodiment
Now the spectral method of detection of Fructus Mori antioxidant activity is elaborated as follows：
(1) 40 parts of the different fresh Fructus Mori of anthocyanidin content are taken.Per part of sample is gathered by Hyperspectral imager
The high spectrum image of 920nm-1660nm, comprises the following steps that：
A, Fructus Mori are placed on mobile platform, adjustment light source is just to Fructus Mori；
B, mobile platform is manipulated by computer software moving, the scanning of EO-1 hyperion camera line obtains the height of whole Fructus Mori
Spectrum picture.
(2) the antioxidant activity reference value of 40 parts of Fructus Mori samples is obtained using DPPH method, and concrete operation step is as follows：
A, will crush after the frost of per part of Fructus Mori sample liquid nitrogen；
B, 0.50g sample is accurately weighed, 5ml methanol extract liquid is added, lucifuge extracts 12 hours at 4 DEG C, afterwards
4000rpm centrifugation takes supernatant in 20 minutes；
C, configuration variable concentrations gradient (0.1,0.08,0.06,0.04,0.02,0.01,0mg/ml) vitamin C methanol
Solution is contrast solution；
D, addition 3.900ml DPPH methanol solution (60uM) in 0.100ml extracting solution (or contrast solution).
E, standing determine absorbance of the solution under 517nm after 60 minutes.
F, the absorbance with contrast solution under 517nm are as X-axis, and the vitamin C concentration of contrast solution is Y-axis, draws mark
Directrix curve, draws regression equation.According to the antioxidant activity of the regression equation calculation Fructus Mori sample extracting solution of standard curve, then change
Calculation is the antioxidant activity of per gram of Fructus Mori fresh fruit.
(3) matlab software programming is adopted, is extracted in the Fructus Mori sample high spectrum image for gathering from step (1) respectively every
The spectral reflectance of individual sample be used for input, the antioxidant activity reference value for being obtained using DPPH method with step (2) for export,
Characteristic wavelength is extracted using successive projection algorithm (SPA) algorithm, referring to Fig. 3, obtain characteristic wavelength for 941nm, 1460nm and
1659nm.And multiple linear regression (MLR) model is set up, model is：
Y=14.6875-16.3270 × X941+163.1246×X1460-83.3823×X1659
Wherein, Y is Fructus Mori antioxidant activity (unit：μm ol/g), with vitamin C as equivalent；
XnMeansigma methodss for the reflectivity of each pixel under n nm of Fructus Mori in high spectrum image.
(4) 20 parts of Fructus Mori to be measured are taken, high spectrum image is gathered by Hyperspectral imager, extract the spectrum of characteristic wavelength
Data, the model according to step (3) calculates antioxidant activity predictive value.
In order to model accuracy is verified, the antioxidant activity reference value of Fructus Mori to be measured is determined using the method for step (2), with
Model prediction antioxidant activity is compared, and the results are shown in Table 1 and Fig. 4.Statistical analysiss show the coefficient of determination (r of forecast model2)
For 0.9852, the root-mean-square error (RMSEP) of predictive value is 0.4131 μm of ol/g.
The Fructus Mori antioxidant activity predictive value to be measured of table 1 and reference value
| Sequence number | Antioxidant activity predictive value (μm ol/g) | Antioxidant activity reference value (μm ol/g) |
| 1 | 2.08 | 2.04 |
| 2 | 2.19 | 2.26 |
| 3 | 4.12 | 4.29 |
| 4 | 4.23 | 4.50 |
| 5 | 4.25 | 4.01 |
| 6 | 4.26 | 4.30 |
| 7 | 4.26 | 4.21 |
| 8 | 4.29 | 4.35 |
| 9 | 4.39 | 4.22 |
| 10 | 4.40 | 4.42 |
| 11 | 4.40 | 4.41 |
| 12 | 4.48 | 4.26 |
| 13 | 6.63 | 6.73 |
| 14 | 7.16 | 7.29 |
| 15 | 7.40 | 7.15 |
| 16 | 7.48 | 7.22 |
| 17 | 7.62 | 7.46 |
| 18 | 7.62 | 7.59 |
| 19 | 7.80 | 8.00 |
| 20 | 8.76 | 8.66 |
It can be seen that multiple linear regression model of the present invention has preferable prediction effect, Fructus Mori to be measured can be effectively distinguished
The height of antioxidant activity, so as to carry out Quality Detection and classification.
Claims (3)
1. a kind of spectral method of detection of Fructus Mori antioxidant activity, 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 determine Fructus Mori sample antioxidant activity as reference value；
In c, the extraction high spectrum image, the information of characteristic wavelength is input, and the antioxidant activity reference value with Fructus Mori sample is
Output, sets up multiple linear regression model；
D, the spectrum picture for gathering under Fructus Mori 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 to be measured
The antioxidant activity of Fructus Mori.
2. the spectral method of detection of Fructus Mori antioxidant activity as claimed in claim 1, it is characterised in that the feature in step c
Wavelength is 941nm, 1460nm and 1659nm.
3. the spectral method of detection of Fructus Mori antioxidant activity as claimed in claim 2, it is characterised in that built by Fructus Mori sample
Vertical multiple linear regression model is as follows：
Y=14.6875-16.3270 × X941+163.1246×X1460-83.3823×X1659
Wherein, Y is Fructus Mori antioxidant activity, unit：μm ol/g, with vitamin C as equivalent；
XnMeansigma methodss for the reflectivity of each pixel under n nm of Fructus Mori in high spectrum image.
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| CN201610873376.2A CN106442357A (en) | 2016-09-30 | 2016-09-30 | Spectrum detection method for antioxidant activity of mulberries |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610873376.2A CN106442357A (en) | 2016-09-30 | 2016-09-30 | Spectrum detection method for antioxidant activity of mulberries |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103411973A (en) * | 2013-09-03 | 2013-11-27 | 西北农林科技大学 | Method for measuring anthocyanin content in wine grape pericarp based on hyperspectrum |
| KR101498096B1 (en) * | 2013-11-19 | 2015-03-06 | 대한민국 | Apparatus and method for discriminating of geographical origin of agricutural products using hyperspectral imaging |
| CN104880427A (en) * | 2015-05-29 | 2015-09-02 | 华南理工大学 | Rapid pork product moisture content detection method |
| CN105136686A (en) * | 2015-08-28 | 2015-12-09 | 河南科技大学 | Measurement method for anthocyanin content of purple-leaf plum leaf |
-
2016
- 2016-09-30 CN CN201610873376.2A patent/CN106442357A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103411973A (en) * | 2013-09-03 | 2013-11-27 | 西北农林科技大学 | Method for measuring anthocyanin content in wine grape pericarp based on hyperspectrum |
| KR101498096B1 (en) * | 2013-11-19 | 2015-03-06 | 대한민국 | Apparatus and method for discriminating of geographical origin of agricutural products using hyperspectral imaging |
| CN104880427A (en) * | 2015-05-29 | 2015-09-02 | 华南理工大学 | Rapid pork product moisture content detection method |
| CN105136686A (en) * | 2015-08-28 | 2015-12-09 | 河南科技大学 | Measurement method for anthocyanin content of purple-leaf plum leaf |
Non-Patent Citations (1)
| Title |
|---|
| 吴迪等: "基于高光谱成像技术和连续投影算法检测葡萄果皮花色苷含量", 《食品科学》 * |
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Application publication date: 20170222 |
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