CN109975237A - The quickly method of measurement rice milled rice flour phytic acid - Google Patents
The quickly method of measurement rice milled rice flour phytic acid Download PDFInfo
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- CN109975237A CN109975237A CN201910159517.8A CN201910159517A CN109975237A CN 109975237 A CN109975237 A CN 109975237A CN 201910159517 A CN201910159517 A CN 201910159517A CN 109975237 A CN109975237 A CN 109975237A
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- 241000209094 Oryza Species 0.000 title claims abstract description 125
- 235000007164 Oryza sativa Nutrition 0.000 title claims abstract description 125
- 235000009566 rice Nutrition 0.000 title claims abstract description 125
- 235000013312 flour Nutrition 0.000 title claims abstract description 60
- 239000000467 phytic acid Substances 0.000 title claims abstract description 54
- 235000002949 phytic acid Nutrition 0.000 title claims abstract description 45
- IMQLKJBTEOYOSI-GPIVLXJGSA-N Inositol-hexakisphosphate Chemical compound OP(O)(=O)O[C@H]1[C@H](OP(O)(O)=O)[C@@H](OP(O)(O)=O)[C@H](OP(O)(O)=O)[C@H](OP(O)(O)=O)[C@@H]1OP(O)(O)=O IMQLKJBTEOYOSI-GPIVLXJGSA-N 0.000 title claims abstract description 44
- IMQLKJBTEOYOSI-UHFFFAOYSA-N Phytic acid Natural products OP(O)(=O)OC1C(OP(O)(O)=O)C(OP(O)(O)=O)C(OP(O)(O)=O)C(OP(O)(O)=O)C1OP(O)(O)=O IMQLKJBTEOYOSI-UHFFFAOYSA-N 0.000 title claims abstract description 44
- 229940068041 phytic acid Drugs 0.000 title claims abstract description 44
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000005259 measurement Methods 0.000 title claims abstract description 19
- 230000003595 spectral effect Effects 0.000 claims abstract description 86
- 238000001228 spectrum Methods 0.000 description 26
- 230000000052 comparative effect Effects 0.000 description 8
- 238000002474 experimental method Methods 0.000 description 7
- 238000001035 drying Methods 0.000 description 4
- 238000002329 infrared spectrum Methods 0.000 description 4
- 239000002253 acid Substances 0.000 description 3
- 235000013339 cereals Nutrition 0.000 description 3
- 238000004737 colorimetric analysis Methods 0.000 description 3
- 238000009499 grossing Methods 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 3
- 238000005096 rolling process Methods 0.000 description 3
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000000513 principal component analysis Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- OYPRJOBELJOOCE-UHFFFAOYSA-N Calcium Chemical compound [Ca] OYPRJOBELJOOCE-UHFFFAOYSA-N 0.000 description 1
- 241000196324 Embryophyta Species 0.000 description 1
- 229920002488 Hemicellulose Polymers 0.000 description 1
- FYYHWMGAXLPEAU-UHFFFAOYSA-N Magnesium Chemical compound [Mg] FYYHWMGAXLPEAU-UHFFFAOYSA-N 0.000 description 1
- 241000878006 Miscanthus sinensis Species 0.000 description 1
- HCHKCACWOHOZIP-UHFFFAOYSA-N Zinc Chemical compound [Zn] HCHKCACWOHOZIP-UHFFFAOYSA-N 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000000433 anti-nutritional effect Effects 0.000 description 1
- 229910052791 calcium Inorganic materials 0.000 description 1
- 239000011575 calcium Substances 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 229920002678 cellulose Polymers 0.000 description 1
- 239000001913 cellulose Substances 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000002860 competitive effect Effects 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- CDAISMWEOUEBRE-UHFFFAOYSA-N inositol Chemical group OC1C(O)C(O)C(O)C(O)C1O CDAISMWEOUEBRE-UHFFFAOYSA-N 0.000 description 1
- 229910052742 iron Inorganic materials 0.000 description 1
- RBTARNINKXHZNM-UHFFFAOYSA-K iron trichloride Chemical compound Cl[Fe](Cl)Cl RBTARNINKXHZNM-UHFFFAOYSA-K 0.000 description 1
- 229920005610 lignin Polymers 0.000 description 1
- 238000012417 linear regression Methods 0.000 description 1
- 229910052749 magnesium Inorganic materials 0.000 description 1
- 239000011777 magnesium Substances 0.000 description 1
- 230000014759 maintenance of location Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 229910021645 metal ion Inorganic materials 0.000 description 1
- 238000003801 milling Methods 0.000 description 1
- 235000016709 nutrition Nutrition 0.000 description 1
- 238000010238 partial least squares regression Methods 0.000 description 1
- 125000002467 phosphate group Chemical group [H]OP(=O)(O[H])O[*] 0.000 description 1
- -1 phospho phytate Chemical class 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 238000004611 spectroscopical analysis Methods 0.000 description 1
- 238000010183 spectrum analysis Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000001429 visible spectrum Methods 0.000 description 1
- 229910052725 zinc Inorganic materials 0.000 description 1
- 239000011701 zinc 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
-
- 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
- G01N2021/3572—Preparation of samples, e.g. salt matrices
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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 kind of methods of quickly measurement rice milled rice flour phytic acid, will be shelled, be milled after the sunning of the mature rice paddy seed as sample to be tested, to obtain rice milled rice flour；It is further comprising the steps of: rice milled rice flour is packed into XDS quick analytic instrument in automatically scanning in 400~2500nm wave-length coverage；To obtain spectral reflectance light numerical value corresponding to characteristic wavelength；Resulting spectral reflectance light numerical value is substituted into formula, to obtain phytic acid content Y in rice milled rice flourPhytic acid content.Finding speed can be accelerated using this method, reduce cost of determination.
Description
Technical field
The present invention relates to the methods of measurement rice milled rice flour phytic acid.
Background technique
Phytic acid also known as phospho phytate, molecular formula C6H18O24, basic structure is by an inositol ring and six phosphate group groups
At there is extremely strong sequestering power, can be combined with the metal ions such as calcium, magnesium, zinc, iron, form complex compound one kind not soluble in water
Anti-nutritional factors and an important indicator of cereal nutritional quality detection, are widely present in crop kernel.Rice is the world
One of upper most important cereal crops, and polished rice is the major part that the mankind eat rice, the phytic acid content understood in polished rice is aobvious
It obtains particularly important.The method that conventional measurement is colonized acid content is time-consuming, pollution environment and higher to operator's technical requirements.Therefore,
A kind of simple, fast and efficient measuring method is necessary.
It is increasingly mature with near-infrared spectrum technique, corresponding mould is established to grain quality index determining using the technology
Type is more and more common.Such as Jin etc. (2017) determines cellulose, the hemicellulose of Chinese silvergrass stalk using near-infrared spectrum technique
Element and content of lignin.Compared with conventional analytical techniques, near-infrared spectral analysis technology, can be by the simple scanning to sample
Short time obtains the index of correlation of sample, and tested sample dosage is few, pollution-free, rapidly and efficiently.So far, not yet related to utilize
The report of near-infrared spectrum technique measurement rice milled rice flour phytic acid content.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of methods of quickly measurement rice milled rice flour phytic acid, using the party
Method can accelerate finding speed, reduce cost of determination.
In order to solve the above technical problem, the present invention provides a kind of methods of quickly measurement rice milled rice flour phytic acid, will make
To be shelled, being milled after the mature rice paddy seed sunning of sample to be tested, to obtain rice milled rice flour；It is further comprising the steps of:
1) rice milled rice flour, is packed into XDS quick analytic instrument in automatically scanning in 400~2500nm wave-length coverage；
To obtain spectral reflectance light numerical value corresponding to following characteristics wavelength:
404、406、436、438、440、466、468、470、520、1110、1112、1114、1396、1398、1400、
1402、1714、1716、1718、1720、1722、1724、1920、1922、2016、2018、2020、2022、2156、 2158、
2160,2162,2164,2166,2168,2388nm；
Note: above-mentioned spectra values are directly scanned acquisition by near infrared spectrometer；
2) the resulting spectral reflectance light numerical value of step 1), is substituted into following formula:
YPhytic acid content=0.9645+4.337 λ404+4.532λ406+1.562λ436+1.367λ438+1.174λ440-1.460λ466 -
1.478λ468-1.479λ470+2.049λ520-4.230λ1110-4.302λ1112-4.364λ1114-4.041λ1396-3.938λ1398-
3.747λ1400-3. 450λ1402+3.057λ1714-3.289λ1716+3.443λ1718+3.539λ1720+3.571λ1722+3.514λ1724
+3.202λ1920+3.698λ1922 -4.132λ2016-3.343λ2018-2.501λ2020-1.627λ2022-0.597λ2156-1.450
λ2158-2.259λ2160-3.012λ2162-3.710λ2164- 4.337λ2166-4.905λ2168+14.759λ2388；
To obtain phytic acid content Y in rice milled rice flourPhytic acid content, unit %.
For example, phytic acid contained in 0.329% i.e. 100g milled rice flour is 0.329g.
The improvement of method as quick measurement rice milled rice flour phytic acid of the invention:
In the step 1), 4 ± 0.2g of rice milled rice flour is packed into the circle of XDS quick analytic instrument (production of FOSS company)
In sample cell (sample cell diameter is 35mm, depth 18mm), automatically scanning (32 times) in 400~2500nm wave-length coverage,
Between be divided into 2nm.
Further improvements in methods as quick measurement rice milled rice flour phytic acid of the invention:
It is first that rice milled rice flour is dry to constant weight in the step 1), it is reloaded into XDS quick analytic instrument.
Further improvements in methods as quick measurement rice milled rice flour phytic acid of the invention:
It is in the step 1), rice milled rice flour is dry to constant weight in 50 ± 5 DEG C (drying time is about 10 hours).
Further improvements in methods as quick measurement rice milled rice flour phytic acid of the invention:
Each resulting rice milled rice flour of sample to be tested repeats progress step 1) 2~3 times, takes each characteristic wavelength institute right
The average value for the spectral reflectance light numerical value answered；
Above-mentioned average value is substituted into the resulting formula of step 2).
Specific step is as follows for invention process of the invention:
(1) 298 parts of mature rice paddy seeds are randomly selected as experimental material, under natural conditions after sunning (2d), are taken off
Shell, (40 mesh) processing of milling, be milled and be sieved obtain rice milled rice flour, as sample.
(2) it after sample drying to constant weight, will be fitted into the circular sample pond of XDS quick analytic instrument of FOSS company production
(sample cell diameter be 35mm, depth 18mm), automatically scanning 32 times in 400~2500nm wave-length coverage are divided into 2 nm.
For the consistency for controlling sample, the sample-loading amount of milled rice flour sample is about 4g.The spectrum of every part of sample is 3 times measured, finally makes even
Mean value carries out Vis/NIR analysis as sample spectra.
(3) ratio with 2:1 in 298 parts of samples is randomly divided into modeling collection and forecast set, wherein 199 parts of milled rice flour samples
This is used to establish calibration model, and 99 parts of samples are verified for model prediction.
(4) principal component analysis is carried out to the Vis/NIR of milled rice flour sample, and to calibration set and verifying collection sample
Spectrum situation be compared (Fig. 1).The first, second, third principal component accounts for 84%, 11%, 4% respectively in milled rice flour spectrum,
For the accumulative variance contribution ratio of first three principal component up to 99%, the calibration set spectral information of milled rice flour sample almost can cover verifying
The spectral information for collecting sample illustrates that the division of calibration set and verifying collection is reasonable from the point of view of the distribution of sample spectra information.
(5) original spectrum that scanning obtains is pre-processed (Fig. 2) using rolling average exponential smoothing, reduces background noise,
Spectrum peak valley is more obvious.
(6) it is measured polished rice matter acid content using using ferric trichloride colorimetric method, concrete content is shown in Table 1.
Phytic acid content counts in 1 sample of table
(7) it is simplified model, improves modeling speed, using competitive adaptive weighted algorithm (CARS) from milled rice flour sample
Vis/NIR wave band screen characteristic wavelength, analyze the correlation of each wavelength with phytic acid content.In milled rice flour sample
36 characteristic wavelengths are screened in the full spectral band of product for model creation, the characteristic wavelength for screening acquisition is as follows: 404,
406、 436、438、440、466、468、470、520、1110、1112、1114、1396、1398、1400、1402、1714、
1716、1718、1720、1722、1724、1920、1922、2016、2018、2020、2022、2156、2158、2160、 2162、
2164、2166、2168、2388nm。
(8) spectrum that diffuses using sample based on 36 characteristic wavelengths is contained as independent variable with the phytic acid of the sample of measurement
Amount is dependent variable, fits spectroscopic data and phytic acid content measured value using PLS (Partial Least Squares), establishes based on 36 spies
The multiple linear regression model of wavelength is levied, the calibration set coefficient of determination has reached 0.9552, established corresponding rice phytic acid content
Model (Fig. 3).
(9) by above-mentioned steps 2) the data obtained substitutes into following moisture content calculation formula, to obtain milled rice flour plant to be measured
Acid content；
YPhytic acid content=0.9645+4.337 λ404+4.532λ406+1.562λ436+1.367λ438+1.174λ440-1.460λ466 -
1.478λ468-1.479λ470+2.049λ520-4.230λ1110-4.302λ1112-4.364λ1114-4.041λ1396-3.938λ1398-
3.747λ1400-3. 450λ1402+3.057λ1714-3.289λ1716+3.443λ1718+3.539λ1720+ 3.571λ1722+3.514
λ1724+3.202λ1920+3.698λ1922-4.132λ2016-3.343λ2018-2.501λ2020-1.627λ2022-0.597λ2156 -
1.450λ2158-2.259λ2160-3.012λ2162-3.710λ2164-4.337λ2166-4.905λ2168+14.759λ2388。
Wherein YPhytic acid contentIt is gram of contained phytic acid in every 100 grams of rice milled rice flours for the phytic acid content of rice milled rice flour to be measured
Number, λ404The spectral reflectance light numerical value for being the sample at 404nm, λ406The spectral reflectance light numerical value for being the sample at 406nm,
λ436The spectral reflectance light numerical value for being the sample at 436nm, λ438The spectral reflectance light numerical value for being the sample at 438nm, λ440
The spectral reflectance light numerical value for being the sample at 440nm, λ466The spectral reflectance light numerical value for being the sample at 466nm, λ468For
Spectral reflectance light numerical value of the sample at 468nm, λ470The spectral reflectance light numerical value for being the sample at 470nm, λ520For this
Spectral reflectance light numerical value of the sample at 520nm, λ1110The spectral reflectance light numerical value for being the sample at 1110nm, λ1112For this
Spectral reflectance light numerical value of the sample at 1112nm, λ1114The spectral reflectance light numerical value for being the sample at 1114nm, λ1396For this
Spectral reflectance light numerical value of the sample at 1396nm, λ1398The spectral reflectance light numerical value for being the sample at 1398nm, λ1400For this
Spectral reflectance light numerical value of the sample at 1400nm, λ1402The spectral reflectance light numerical value for being the sample at 1402nm, λ1714For this
Spectral reflectance light numerical value of the sample at 1714nm, λ1716The spectral reflectance light numerical value for being the sample at 1716nm, λ1718For this
Spectral reflectance light numerical value of the sample at 1718nm, λ1720The spectral reflectance light numerical value for being the sample at 1720nm, λ1722For this
Spectral reflectance light numerical value of the sample at 1722nm, λ1724The spectral reflectance light numerical value for being the sample at 1724nm, λ1920For this
Spectral reflectance light numerical value of the sample at 1920nm, λ1922The spectral reflectance light numerical value for being the sample at 1922, λ2016For the sample
Originally the spectral reflectance light numerical value at 2016nm, λ2018The spectral reflectance light numerical value for being the sample at 2018nm, λ2020For the sample
Originally the spectral reflectance light numerical value at 2020nm, λ2022The spectral reflectance light numerical value for being the sample at 2022nm, λ2156For the sample
Originally the spectral reflectance light numerical value at 2156nm, λ2158The spectral reflectance light numerical value for being the sample at 2158nm, λ2160For the sample
Originally the spectral reflectance light numerical value at 2160nm, λ2162The spectral reflectance light numerical value for being the sample at 2162nm, λ2164For the sample
Originally the spectral reflectance light numerical value at 2164nm, λ2166The spectral reflectance light numerical value for being the sample at 2166nm, λ2168For the sample
Originally the spectral reflectance light numerical value at 2168nm, λ2388The spectral reflectance light numerical value for being the sample at 2388nm.
(10) reflected light for extracting 36 characteristic wave strong points of 99 parts of milled rice flours, can get corresponding phytic acid content.Prediction
The coefficient of determination that the true value of collection and the coefficient of determination of predicted value are and verify collection has reached 0.9500.It is special based on milled rice flour sample
The fitting effect of the phytic acid content model predication value and actual measured value of levying spectrum is good (Fig. 3).
Common near infrared light spectral coverage (1100-2500nm) in similar techniques at present, and the spectrum that the present invention uses is
400-2500nm, relative to above-mentioned common near infrared light spectral coverage (1100-2500nm), range is broader, and covers portion
Divide visible spectrum.When finding characteristic spectrum with CARS, have 404,406,436,438,440,466,468,470,520nm totally 9
A spectrum is fallen in except (1100-2500nm), therefore the model that the present invention establishes is relatively reliable.
In modeling process, because the data volume of all band spectrum is often very big, the spectrum of a sample in the present invention
Just contain 1050 wavelength variables.Since near infrared spectrum has the characteristics that absorption intensity is weak, is overlapped serious interference between bands of a spectrum,
When being modeled using whole spectral wavelength variables, it may appear that model is complicated, computationally intensive and irrelevant variable will affect model
Precision of prediction the problems such as.To solve the above problems, all band wavelength is in optimized selection in the present invention, it is accurate to model to find
Property has the wavelength variable of significant contribution.
Inventor has found during invention: if only set spectrum in 1100-2500nm, that is, cancel 404,406,
436,438,440,466,468, the 470, use of 520nm totally 9 spectrum；It is in optimized selection in any case, will lead to institute
Obtain phytic acid content Y in rice milled rice flourPhytic acid contentBetween truthful data (i.e. according to traditional phytic acid measuring method -- ferric trichloride colorimetric
Method acquired results) there is biggish deviation, deviation ratio is about 20~30%.
The present invention has following technical advantage:
1, this method step is simple, and the rice milled rice flour that can fetch water is scanned, and by fitting PLS regression model, directly obtains
Obtain milled rice flour phytic acid content；
2, this method is quickly, to need not move through the standard curve making of extraction, chelatropic reaction and complexity that time-consuming etc. many
Step, milled rice flour sample dosage is few, and non-environmental-pollution.
3, this method has chosen the near infrared light spectrum of 36 characteristic peaks closely related with rice milled rice flour phytic acid, scanning
Time is shorter.
To sum up, the present invention provides a kind of sides of quick detection rice milled rice flour phytic acid content based on 36 characteristic wavelengths
Method can accelerate finding speed, reduce cost of determination.
Detailed description of the invention
Specific embodiments of the present invention will be described in further detail with reference to the accompanying drawing.
Fig. 1 is the spectrum principal component analysis figure of milled rice flour sample；
Dot represents calibration set sample, and square represents verifying collection sample.
Fig. 2 is sample original spectrum and through rolling average exponential smoothing treated spectrum；
A, B distinguishes the primary light spectrogram of milled rice flour sample and through rolling average exponential smoothing treated sample spectrum diagram.
Fig. 3 is the dependency graph of phytic acid content calibration model predicted value and measured value based on characteristic wavelength；
Square represents calibration set, and dot represents verifying collection.
Specific embodiment
The present invention is described further combined with specific embodiments below, but protection scope of the present invention is not limited in
This:
Embodiment 1, a kind of method of quickly measurement rice milled rice flour phytic acid, comprising the following steps:
1), according to routine techniques, will first be dried as the mature rice paddy seed of sample to be tested (generally sunning 2d), then into
Row shelling is milled, and be milled and be sieved (40 mesh) processing, obtains rice milled rice flour.
2), by 4g rice milled rice flour, drying to constant weight (drying time is about 10 hours) in 50 DEG C；It is raw to be packed into FOSS company
In the circular sample pond (sample cell diameter is 35mm, depth 18mm) of the XDS quick analytic instrument of production, in 400~2500nm wave
Automatically scanning 32 times in long range, are divided into 2nm；
To obtain spectral reflectance light numerical value corresponding to following characteristics wavelength:
404、406、436、438、440、466、468、470、520、1110、1112、1114、1396、1398、1400、
1402、1714、1716、1718、1720、1722、1724、1920、1922、2016、2018、2020、2022、2156、2158、
2160,2162,2164,2166,2168,2388nm；
3), the resulting rice milled rice flour of each sample to be tested repeats step 2) 2 times (that is, scanning carries out 3 times altogether), takes
The average value of 3 spectral reflectance light numerical value corresponding to each characteristic wavelength；
Above-mentioned average value is substituted into following step 4) resulting formula.
4) average value of the resulting spectral reflectance light numerical value of step 3), is substituted into following formula:
YPhytic acid content=0.9645+4.337 λ404+4.532λ406+1.562λ436+1.367λ438+1.174λ440-1.460λ466 -
1.478λ468-1.479λ470+2.049λ520-4.230λ1110-4.302λ1112-4.364λ1114-4.041λ1396-3.938λ1398-
3.747λ1400-3. 450λ1402+3.057λ1714-3.289λ1716+3.443λ1718+3.539λ1720+3.571λ1722+3.514λ1724
+3.202λ1920+3.698λ1922 -4.132λ2016-3.343λ2018-2.501λ2020-1.627λ2022-0.597λ2156-1.450
λ2158-2.259λ2160-3.012λ2162-3.710λ2164- 4.337λ2166-4.905λ2168+14.759λ2388；
To obtain phytic acid content in rice milled rice flour.
Wherein YPhytic acid contentFor the phytic acid content of rice milled rice flour to be measured, λ4043 spectral reflectances for being the sample at 404nm
The average value of light numerical value, λ406The average value for 3 spectral reflectance light numerical value for being the sample at 406nm, λ436Exist for the sample
The average value of 3 spectral reflectance light numerical value at 436nm, λ4383 spectral reflectance light numerical value for being the sample at 438nm
Average value, λ440The average value for 3 spectral reflectance light numerical value for being the sample at 440nm, λ466It is the sample at 466nm
3 spectral reflectance light numerical value average value, λ468The average value for 3 spectral reflectance light numerical value for being the sample at 468nm,
λ470The average value for 3 spectral reflectance light numerical value for being the sample at 470nm, λ5203 light for being the sample at 520nm
Compose the average value of reflected light numerical value, λ1110The average value for 3 spectral reflectance light numerical value for being the sample at 1110nm, λ1112For
The average value of 3 spectral reflectance light numerical value of the sample at 1112nm, λ11143 spectrum for being the sample at 1114nm are anti-
Penetrate the average value of light numerical value, λ1396The average value for 3 spectral reflectance light numerical value for being the sample at 1396nm, λ1398For the sample
Originally the average value of the 3 spectral reflectance light numerical value at 1398nm, λ14003 spectral reflectance light for being the sample at 1400nm
The average value of numerical value, λ1402The average value for 3 spectral reflectance light numerical value for being the sample at 1402nm, λ1714Exist for the sample
The average value of 3 spectral reflectance light numerical value at 1714nm, λ17163 spectral reflectance light numerical value for being the sample at 1716nm
Average value, λ1718The average value for 3 spectral reflectance light numerical value for being the sample at 1718nm, λ1720Exist for the sample
The average value of 3 spectral reflectance light numerical value at 1720nm, λ17223 spectral reflectance light numerical value for being the sample at 1722nm
Average value, λ1724The average value for 3 spectral reflectance light numerical value for being the sample at 1724nm, λ1920Exist for the sample
The average value of 3 spectral reflectance light numerical value at 1920nm, λ19223 spectral reflectance light numerical value for being the sample at 1922
Average value, λ2016The average value for 3 spectral reflectance light numerical value for being the sample at 2016nm, λ2018It is the sample in 2018nm
The average value of the 3 spectral reflectance light numerical value at place, λ20203 spectral reflectance light numerical value for being the sample at 2020nm are averaged
Value, λ2022The average value for 3 spectral reflectance light numerical value for being the sample at 2022nm, λ2156Be the sample at 2156nm 3
The average value of a spectral reflectance light numerical value, λ2158The average value for 3 spectral reflectance light numerical value for being the sample at 2158nm,
λ2160The average value for 3 spectral reflectance light numerical value for being the sample at 2160nm, λ21623 for being the sample at 2162nm
The average value of spectral reflectance light numerical value, λ2164The average value for 3 spectral reflectance light numerical value for being the sample at 2164nm, λ2166
The average value for 3 spectral reflectance light numerical value for being the sample at 2166nm, λ21683 spectrum for being the sample at 2168nm
The average value of reflected light numerical value, λ2388The average value for 3 spectral reflectance light numerical value for being the sample at 2388nm.
Experiment one, by as the mature rice paddy seed of sample to be tested (Zhejiang agriculture 41, Zhejiang agricultural university 104, middle silk 3, it is good educate 293,
Hangzhoupro 112-07, platform morning 12-41) according to 1 the method for embodiment it is measured milled rice flour phytic acid, acquired results are described in table 2 below.
Confirmatory experiment, by above-mentioned mature rice paddy seed according to current traditional phytic acid measuring method --- ferric trichloride colorimetric method
It is detected, acquired results are as described in Table 2.
Table 2
Note: 0.311%, i.e. phytic acid contained in 100g milled rice flour is 0.311g.
For acquired results of the present invention for confirmatory experiment acquired results, deviation ratio is only 0.1%~1.5%.
520 in 36 characteristic wavelengths of 1 step 2) of embodiment are changed to 880 by comparative example 1；λ in step 3) formula520
Also it is changed to λ accordingly880；Remaining is equal to embodiment 1.
1402 in 36 characteristic wavelengths of 1 step 2) of embodiment are changed to common 1522 by comparative example 2；Step 3) is public
λ in formula1402Also it is changed to λ accordingly1522；Remaining is equal to embodiment 1.
1722 in 36 characteristic wavelengths of 1 step 2) of embodiment are changed to common 1850 by comparative example 3；Step 3) is public
λ in formula1722Also it is changed to λ accordingly1850；Remaining is equal to embodiment 1.
By the mature rice paddy seed of same experiment one (Zhejiang agricultural university 104, good educates 293 at middle silk 3) according to above-mentioned comparative example 1~
3 the method for comparative example is detected, and acquired results are described in table 3 below.
Table 3
For 1 acquired results of comparative example for confirmatory experiment acquired results, deviation ratio is respectively 8%, 4.1%, 3%；
2 acquired results of comparative example for confirmatory experiment acquired results, deviation ratio is respectively 23%, 3.4%,
9.7%；
3 acquired results of comparative example for confirmatory experiment acquired results, deviation ratio is respectively 7.5%, 4.8%,
4%.
Therefore it can be seen that using 36 nearly characteristic light spectrum quick test rice milled rice flour phytic acid being fast and effective in the present invention
Conclusion.
The above list is only a few specific embodiments of the present invention for finally, it should also be noted that.Obviously, this hair
Bright to be not limited to above embodiments, acceptable there are many deformations.Those skilled in the art can be from present disclosure
All deformations for directly exporting or associating, are considered as protection scope of the present invention.
Claims (5)
1. the quickly method of measurement rice milled rice flour phytic acid will take off after the sunning of the mature rice paddy seed as sample to be tested
Shell is milled, to obtain rice milled rice flour；It is characterized in that the following steps are included:
1) rice milled rice flour, is packed into XDS quick analytic instrument in automatically scanning in 400~2500nm wave-length coverage；
To obtain spectral reflectance light numerical value corresponding to following characteristics wavelength:
404、406、436、438、440、466、468、470、520、1110、1112、1114、1396、1398、1400、1402、
1714、1716、1718、1720、1722、1724、1920、1922、2016、2018、2020、2022、2156、2158、2160、
2162,2164,2166,2168,2388nm；
2) the resulting spectral reflectance light numerical value of step 1), is substituted into following formula:
YPhytic acid content=0.9645+4.337 λ404+4.532λ406+1.562λ436+1.367λ438+1.174λ440-1.460λ466-1.478
λ468-1.479λ470+2.049λ520-4.230λ1110-4.302λ1112-4.364λ1114-4.041λ1396-3.938λ1398-3.747
λ1400-3.450λ1402+3.057λ1714-3.289λ1716+3.443λ1718+3.539λ1720+3.571λ1722+3.514λ1724+3.202
λ1920+3.698λ1922-4.132λ2016-3.343λ2018-2.501λ2020-1.627λ2022-0.597λ2156-1.450λ2158-2.259
λ2160-3.012λ2162-3.710λ2164-4.337λ2166-4.905λ2168+14.759λ2388；
To obtain phytic acid content Y in rice milled rice flourPhytic acid content。
2. the method for quick measurement rice milled rice flour phytic acid according to claim 1, it is characterized in that:
In the step 1), 4 ± 0.2g of rice milled rice flour is fitted into the circular sample pond of XDS quick analytic instrument, 400~
Automatically scanning in 2500nm wave-length coverage, is divided into 2nm.
3. the method for quick measurement rice milled rice flour phytic acid according to claim 1 or 2, it is characterized in that:
It is first that rice milled rice flour is dry to constant weight in the step 1), it is reloaded into XDS quick analytic instrument.
4. the method for quick measurement rice milled rice flour phytic acid according to claim 3, it is characterized in that:
It is in the step 1), rice milled rice flour is dry to constant weight in 50 ± 5 DEG C.
5. the method for quick measurement rice milled rice flour phytic acid according to any one of claims 1 to 4, it is characterized in that:
Each resulting rice milled rice flour of sample to be tested repeats progress step 1) 2~3 times, takes corresponding to each characteristic wavelength
The average value of spectral reflectance light numerical value；
Above-mentioned average value is substituted into the resulting formula of step 2).
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015010084A1 (en) * | 2013-07-19 | 2015-01-22 | Verenium Corporation | Colorimetric phytic acid assay |
| CN105181643A (en) * | 2015-10-12 | 2015-12-23 | 华中农业大学 | Near-infrared inspection method for rice quality and application thereof |
| CN106018337A (en) * | 2016-08-04 | 2016-10-12 | 浙江大学 | Method for determination of phytic acid content of cotton seed powder |
| CN106092955A (en) * | 2016-05-26 | 2016-11-09 | 浙江大学 | The assay method of awns platymiscium leaf water content |
| CN109406447A (en) * | 2018-10-23 | 2019-03-01 | 中粮营养健康研究院有限公司 | A kind of near infrared detection method of tannin in sorghum |
-
2019
- 2019-03-04 CN CN201910159517.8A patent/CN109975237A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2015010084A1 (en) * | 2013-07-19 | 2015-01-22 | Verenium Corporation | Colorimetric phytic acid assay |
| CN105181643A (en) * | 2015-10-12 | 2015-12-23 | 华中农业大学 | Near-infrared inspection method for rice quality and application thereof |
| CN106092955A (en) * | 2016-05-26 | 2016-11-09 | 浙江大学 | The assay method of awns platymiscium leaf water content |
| CN106018337A (en) * | 2016-08-04 | 2016-10-12 | 浙江大学 | Method for determination of phytic acid content of cotton seed powder |
| CN109406447A (en) * | 2018-10-23 | 2019-03-01 | 中粮营养健康研究院有限公司 | A kind of near infrared detection method of tannin in sorghum |
Non-Patent Citations (1)
| Title |
|---|
| 周军琴: "基于近红外光谱技术快速检测稻米营养品质和加工精度的研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅰ辑》 * |
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