CN105588817A - Milk freshness detecting method based on multisource spectroscopic data fusion - Google Patents
Milk freshness detecting method based on multisource spectroscopic data fusion Download PDFInfo
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- CN105588817A CN105588817A CN201510941205.4A CN201510941205A CN105588817A CN 105588817 A CN105588817 A CN 105588817A CN 201510941205 A CN201510941205 A CN 201510941205A CN 105588817 A CN105588817 A CN 105588817A
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- 239000008267 milk Substances 0.000 title claims abstract description 97
- 210000004080 milk Anatomy 0.000 title claims abstract description 97
- 235000013336 milk Nutrition 0.000 title claims abstract description 97
- 230000004927 fusion Effects 0.000 title claims abstract description 26
- 238000000034 method Methods 0.000 title claims abstract description 17
- 238000004611 spectroscopical analysis Methods 0.000 title claims abstract description 9
- 238000001228 spectrum Methods 0.000 claims abstract description 30
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 27
- 238000001237 Raman spectrum Methods 0.000 claims abstract description 26
- HEMHJVSKTPXQMS-UHFFFAOYSA-M Sodium hydroxide Chemical compound [OH-].[Na+] HEMHJVSKTPXQMS-UHFFFAOYSA-M 0.000 claims description 33
- 230000003287 optical effect Effects 0.000 claims description 13
- 239000012086 standard solution Substances 0.000 claims description 12
- 230000005540 biological transmission Effects 0.000 claims description 6
- KJFMBFZCATUALV-UHFFFAOYSA-N phenolphthalein Chemical compound C1=CC(O)=CC=C1C1(C=2C=CC(O)=CC=2)C2=CC=CC=C2C(=O)O1 KJFMBFZCATUALV-UHFFFAOYSA-N 0.000 claims description 6
- 230000003595 spectral effect Effects 0.000 claims description 6
- 230000003044 adaptive effect Effects 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 claims description 3
- 238000003556 assay Methods 0.000 claims description 3
- 238000004821 distillation Methods 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 230000007935 neutral effect Effects 0.000 claims description 3
- 238000007500 overflow downdraw method Methods 0.000 claims description 3
- 238000010238 partial least squares regression Methods 0.000 claims description 3
- 238000004448 titration Methods 0.000 claims description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 3
- DGAQECJNVWCQMB-PUAWFVPOSA-M Ilexoside XXIX Chemical compound C[C@@H]1CC[C@@]2(CC[C@@]3(C(=CC[C@H]4[C@]3(CC[C@@H]5[C@@]4(CC[C@@H](C5(C)C)OS(=O)(=O)[O-])C)C)[C@@H]2[C@]1(C)O)C)C(=O)O[C@H]6[C@@H]([C@H]([C@@H]([C@H](O6)CO)O)O)O.[Na+] DGAQECJNVWCQMB-PUAWFVPOSA-M 0.000 claims 1
- 238000010790 dilution Methods 0.000 claims 1
- 239000012895 dilution Substances 0.000 claims 1
- 229910052708 sodium Inorganic materials 0.000 claims 1
- 239000011734 sodium Substances 0.000 claims 1
- OYPRJOBELJOOCE-UHFFFAOYSA-N Calcium Chemical compound [Ca] OYPRJOBELJOOCE-UHFFFAOYSA-N 0.000 description 3
- 229910052791 calcium Inorganic materials 0.000 description 3
- 239000011575 calcium Substances 0.000 description 3
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 1
- ZOKXTWBITQBERF-UHFFFAOYSA-N Molybdenum Chemical compound [Mo] ZOKXTWBITQBERF-UHFFFAOYSA-N 0.000 description 1
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 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
- 239000008280 blood Substances 0.000 description 1
- 210000004369 blood Anatomy 0.000 description 1
- MWKXCSMICWVRGW-UHFFFAOYSA-N calcium;phosphane Chemical compound P.[Ca] MWKXCSMICWVRGW-UHFFFAOYSA-N 0.000 description 1
- 229910052802 copper Inorganic materials 0.000 description 1
- 239000010949 copper Substances 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 229910052500 inorganic mineral Inorganic materials 0.000 description 1
- 229910052742 iron Inorganic materials 0.000 description 1
- WPBNNNQJVZRUHP-UHFFFAOYSA-L manganese(2+);methyl n-[[2-(methoxycarbonylcarbamothioylamino)phenyl]carbamothioyl]carbamate;n-[2-(sulfidocarbothioylamino)ethyl]carbamodithioate Chemical compound [Mn+2].[S-]C(=S)NCCNC([S-])=S.COC(=O)NC(=S)NC1=CC=CC=C1NC(=S)NC(=O)OC WPBNNNQJVZRUHP-UHFFFAOYSA-L 0.000 description 1
- 239000011707 mineral Substances 0.000 description 1
- 229910052750 molybdenum Inorganic materials 0.000 description 1
- 239000011733 molybdenum Substances 0.000 description 1
- 229910052698 phosphorus Inorganic materials 0.000 description 1
- 239000011574 phosphorus Substances 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 239000011701 zinc Substances 0.000 description 1
- 229910052725 zinc Inorganic materials 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
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/65—Raman scattering
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- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Biochemistry (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Investigating, Analyzing Materials By Fluorescence Or Luminescence (AREA)
Abstract
The invention discloses a milk freshness detecting method based on multisource spectroscopic data fusion. The method comprises the following steps that a plurality of milk samples are collected and divided into the calibration set milk samples and the test set milk samples, the acidity values, near infrared spectrums and Raman spectrums of the milk samples are measured, the preprocessed near infrared spectrums and Raman spectrums are subjected to data layer fusion, and a fused spectrum is obtained; a quantitative model of the acidity values of the calibration set milk samples and the fused spectrum of the calibration set milk samples is established; the acidity values of the test set milk samples are predicted through the quantitative model, and compared with those of the calibration set milk samples; the near infrared spectrum and Raman spectrum of one milk sample to be detected are collected, and the acidity value of the milk sample to be detected is predicted through the quantitative model. The milk freshness detecting method based on multisource spectroscopic data fusion is safe, reliable, fast and accurate and has very high practical application value.
Description
Technical field
The present invention relates to milk detection technique field, be specifically related to a kind of milk Noninvasive Measuring Method of Freshness based on multi-source optical spectrum data fusion.
Background technology
Milk is one of the most ancient natural drink, is described as " white blood ", and the importance of human body is well imagined; Milk contains abundant mineral matter, calcium, phosphorus, iron, zinc, copper, manganese, molybdenum, and milk is human calcium's best source, and calcium phosphorus ration is very suitable, is beneficial to the absorption of calcium. But milk is unfavorable for stored for a long time, the time can be stale once length, just there will be discomfort once people has drunk, and even may have serious consequences.
Summary of the invention
For the weak point existing in above-mentioned technology, the invention provides a kind of safe and reliable, milk Noninvasive Measuring Method of Freshness based on multi-source optical spectrum data fusion fast and accurately.
The technical solution adopted for the present invention to solve the technical problems is: a kind of milk Noninvasive Measuring Method of Freshness based on multi-source optical spectrum data fusion, comprise the steps: step 1, sample collection: gather the same kind milk sample that same date is not produced some, be divided into calibration set milk sample and test set milk sample; Step 2, acidity value are measured: measure the acidity value of calibration set milk sample and test set milk sample, the acidity value scope of milk sample is 20 ° of T～30 ° T; Step 3, spectra collection: near infrared spectrum and the Raman spectrum of acquisition correction collection milk sample and test set milk sample; Step 4, spectroscopic data merge: respectively near infrared spectrum and Raman spectrum are carried out to pretreatment, and pretreated near infrared spectrum and Raman spectrum are carried out to data Layer fusion, obtain merging spectrum; Step 5, quantitative model are set up: the quantitative model of setting up the acidity value of calibration set milk sample and the fusion spectrum of calibration set milk sample; The checking of step 6, quantitative model: by the acidity value of the quantitative model prediction test set milk sample set up in step 4, and with step 2 in the acidity value comparison of the test set milk sample measured, require error≤10%, coefficient correlation >=95%; Step 7, milk sample freshness to be measured are analyzed: gather near infrared spectrum and the Raman spectrum of milk sample to be measured, adopt quantitative model to predict the acidity value of milk sample to be measured; Wherein, in the time of ° T of acidity value >=25, judge that milk sample to be measured is stale; In the time of 25 ° of T of acidity value <, judge that milk sample to be measured is fresh.
Preferably, acidity value assay method in described step 2 is as follows: draw 10ml milk sample and inject 100ml triangular flask, and dilute with 20ml neutral distillation water, add again 0.5% phenolphthalein indicator 0.5ml to mix, adopt the titration of 0.1mol/L standard solution of sodium hydroxide, shake constantly until blush did not disappear in 30 seconds; Wherein, acidity value (° T)=10* (V1-V0) * C; V1 is the volume that consumes standard solution of sodium hydroxide, and unit is ml; V0 consumes the volume of standard solution of sodium hydroxide while being blank test, unit is ml; C is the concentration of standard solution of sodium hydroxide, and unit is mol/L.
Preferably, in described step 3, the acquisition condition of near infrared spectrum is: 20～30 DEG C of milk sample temperature, and spectral region 1200～1800nm, acquisition mode is transmission, repeated acquisition 3 times is also got the near infrared spectrum of its mean value as this milk sample.
Preferably, in described step 3, the acquisition condition of Raman spectrum is: 40 ± 2 DEG C of milk sample temperature, spectrum wave-number range 4000～650cm-1, acquisition mode is transmission, repeated acquisition 3 times is also got the Raman spectrum of its mean value as this milk sample.
Preferably, the spectroscopic data fusion method in described step 4 is: by end to end the abscissa of pretreated near infrared spectrum and Raman spectrum fusion, and share same ordinate, obtain merging spectrum.
Preferably, the near infrared spectrum pretreatment in described step 4 adopts 11 level and smooth spectral noise of eliminating of Savitzky-Golay filtering, and described Raman spectrum pretreatment employing adaptive iteration heavily weighting punishment least-squares algorithm carries out baseline correction.
Preferably, in described step 5, set up quantitative model and adopt PLS regression analysis to set up, require the R of quantitative model2≥0.95，RMSECV≤0.01。
Compared with prior art, its beneficial effect is in the present invention: the milk Noninvasive Measuring Method of Freshness based on multi-source optical spectrum data fusion provided by the invention, and safe and reliable, quick and precisely, there is good actual application value.
Detailed description of the invention
The invention provides a kind of milk Noninvasive Measuring Method of Freshness based on multi-source optical spectrum data fusion, comprise the steps:
Step 1, sample collection: gather the same kind milk sample that same date is not produced some, be divided into calibration set milk sample and test set milk sample;
Step 2, acidity value are measured: the acidity value of measuring calibration set milk sample and test set milk sample, the acidity value scope of milk sample is 20 ° of T～30 ° T, acidity value assay method is as follows: draw 10ml milk sample and inject 100ml triangular flask, and dilute with 20ml neutral distillation water, add again 0.5% phenolphthalein indicator 0.5ml to mix, adopt the titration of 0.1mol/L standard solution of sodium hydroxide, shake constantly until blush did not disappear in 30 seconds; Wherein, acidity value (° T)=10* (V1-V0) * C; V1 is the volume that consumes standard solution of sodium hydroxide, and unit is ml; V0 consumes the volume of standard solution of sodium hydroxide while being blank test, unit is ml; C is the concentration of standard solution of sodium hydroxide, and unit is mol/L;
Step 3, spectra collection: near infrared spectrum and the Raman spectrum of acquisition correction collection milk sample and test set milk sample:
The acquisition condition of near infrared spectrum is: 20～30 DEG C of milk sample temperature, and spectral region 1200～1800nm, acquisition mode is transmission, repeated acquisition 3 times is also got the near infrared spectrum of its mean value as this milk sample;
The acquisition condition of Raman spectrum is: 40 ± 2 DEG C of milk sample temperature, spectrum wave-number range 4000～650cm-1, acquisition mode is transmission, repeated acquisition 3 times is also got the Raman spectrum of its mean value as this milk sample;
Step 4, spectroscopic data merges: respectively near infrared spectrum and Raman spectrum are carried out to pretreatment, near infrared spectrum pretreatment adopts 11 level and smooth spectral noise of eliminating of Savitzky-Golay filtering, described Raman spectrum pretreatment employing adaptive iteration heavily weighting punishment least-squares algorithm carries out baseline correction, and pretreated near infrared spectrum and Raman spectrum are carried out to data Layer fusion, obtain merging spectrum, spectroscopic data fusion method is: by end to end the abscissa of pretreated near infrared spectrum and Raman spectrum fusion, and shared same ordinate, obtain merging spectrum,
Step 5, quantitative model are set up: set up the quantitative model of the acidity value of calibration set milk sample and the fusion spectrum of calibration set milk sample, set up quantitative model and adopt PLS regression analysis to set up, require the R of quantitative model2≥0.95，RMSECV≤0.01；
The checking of step 6, quantitative model: by the acidity value of the quantitative model prediction test set milk sample set up in step 4, and with step 2 in the acidity value comparison of the test set milk sample measured, require error≤10%, coefficient correlation >=95%;
Step 7, milk sample freshness to be measured are analyzed: gather near infrared spectrum and the Raman spectrum of milk sample to be measured, adopt quantitative model to predict the acidity value of milk sample to be measured;
Wherein, in the time of ° T of acidity value >=25, judge that milk sample to be measured is stale; In the time of 25 ° of T of acidity value <, judge that milk sample to be measured is fresh.
Claims (7)
1. the milk Noninvasive Measuring Method of Freshness based on multi-source optical spectrum data fusion, is characterized in that, comprisesFollowing steps:
Step 1, sample collection: gather the same kind milk sample that same date is not produced some, by its pointBecome calibration set milk sample and test set milk sample;
Step 2, acidity value are measured: measure the acidity value of calibration set milk sample and test set milk sample,The acidity value scope of milk sample is 20 ° of T～30 ° T;
Step 3, spectra collection: the near infrared spectrum of acquisition correction collection milk sample and test set milk sampleAnd Raman spectrum;
Step 4, spectroscopic data merge: respectively near infrared spectrum and Raman spectrum are carried out to pretreatment, and willPretreated near infrared spectrum and Raman spectrum carry out data Layer fusion, obtain merging spectrum;
Step 5, quantitative model are set up: acidity value and the calibration set milk sample of setting up calibration set milk sampleThe quantitative model of fusion spectrum;
Step 6, quantitative model checking: by the quantitative model prediction test set milk sample of setting up in step 4The acidity value of product, and with step 2 in the acidity value comparison of the test set milk sample measured, require error≤10%, coefficient correlation >=95%;
Step 7, milk sample freshness to be measured are analyzed: gather the near infrared spectrum of milk sample to be measured and drawGraceful spectrum, adopts quantitative model to predict the acidity value of milk sample to be measured;
Wherein, in the time of ° T of acidity value >=25, judge that milk sample to be measured is stale; As 25 ° of acidity value <When T, judge that milk sample to be measured is fresh.
2. the milk Noninvasive Measuring Method of Freshness based on multi-source optical spectrum data fusion as claimed in claim 1, itsBe characterised in that, the acidity value assay method in described step 2 is as follows: draw 10ml milk sample and inject 100mlIn triangular flask, and with 20ml neutral distillation water dilution, then add 0.5% phenolphthalein indicator 0.5ml to mix, adoptWith the titration of 0.1mol/L standard solution of sodium hydroxide, shake is not until blush disappeared in 30 seconds is constantlyOnly;
Wherein, acidity value (° T)=10* (V1-V0) * C; V1 is the body that consumes standard solution of sodium hydroxideLong-pending, unit is ml; V0 consumes the volume of standard solution of sodium hydroxide while being blank test, unit is ml; CFor the concentration of standard solution of sodium hydroxide, unit is mol/L.
3. the milk Noninvasive Measuring Method of Freshness based on multi-source optical spectrum data fusion as claimed in claim 1, itsBe characterised in that, in described step 3, the acquisition condition of near infrared spectrum is: 20～30 DEG C of milk sample temperature,Spectral region 1200～1800nm, acquisition mode is transmission, repeated acquisition 3 times is also got its mean value as thisThe near infrared spectrum of milk sample.
4. the milk Noninvasive Measuring Method of Freshness based on multi-source optical spectrum data fusion as claimed in claim 1, itsBe characterised in that, in described step 3, the acquisition condition of Raman spectrum is: 40 ± 2 DEG C of milk sample temperature, lightSpectrum wave-number range 4000～650cm-1, acquisition mode is transmission, repeated acquisition 3 times is also got its mean value conductThe Raman spectrum of this milk sample.
5. the milk Noninvasive Measuring Method of Freshness based on multi-source optical spectrum data fusion as claimed in claim 1, itsBe characterised in that, the spectroscopic data fusion method in described step 4 is: by pretreated near infrared spectrum andThe end to end fusion of abscissa of Raman spectrum, and share same ordinate, obtain merging spectrum.
6. the milk Noninvasive Measuring Method of Freshness based on multi-source optical spectrum data fusion as claimed in claim 1, itsBe characterised in that, the near infrared spectrum pretreatment in described step 4 adopts Savitzky-Golay filtering 11 pointsThe level and smooth spectral noise of eliminating, described Raman spectrum pretreatment adopts heavily weighting punishment least square of adaptive iterationAlgorithm carries out baseline correction.
7. the milk Noninvasive Measuring Method of Freshness based on multi-source optical spectrum data fusion as claimed in claim 1, itsBe characterised in that, in described step 5, set up quantitative model and adopt PLS regression analysis to set up, require quantitativelyThe R of model2≥0.95，RMSECV≤0.01。
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Cited By (6)
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| CN106404743A (en) * | 2016-11-01 | 2017-02-15 | 北京华泰诺安技术有限公司 | Raman spectrum and near infrared spectrum combined detection method and detection device |
| CN106770155A (en) * | 2016-11-22 | 2017-05-31 | 武汉轻工大学 | A kind of content of material analysis method |
| CN107328721A (en) * | 2017-06-29 | 2017-11-07 | 深圳市赛亿科技开发有限公司 | A kind of device and method that food security is detected based on multi-source optical spectrum data fusion |
| CN108362659A (en) * | 2018-02-07 | 2018-08-03 | 武汉轻工大学 | Edible oil type method for quick identification based on multi-source optical spectrum parallel connection fusion |
| CN109540838A (en) * | 2019-01-24 | 2019-03-29 | 广东产品质量监督检验研究院（国家质量技术监督局广州电气安全检验所、广东省试验认证研究院、华安实验室） | A kind of method of acidity in quick detection acidified milk |
| CN116559386A (en) * | 2023-05-22 | 2023-08-08 | 淮阴工学院 | Milk freshness detection method based on dielectric spectrum |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106404743A (en) * | 2016-11-01 | 2017-02-15 | 北京华泰诺安技术有限公司 | Raman spectrum and near infrared spectrum combined detection method and detection device |
| CN106770155A (en) * | 2016-11-22 | 2017-05-31 | 武汉轻工大学 | A kind of content of material analysis method |
| CN107328721A (en) * | 2017-06-29 | 2017-11-07 | 深圳市赛亿科技开发有限公司 | A kind of device and method that food security is detected based on multi-source optical spectrum data fusion |
| CN108362659A (en) * | 2018-02-07 | 2018-08-03 | 武汉轻工大学 | Edible oil type method for quick identification based on multi-source optical spectrum parallel connection fusion |
| CN108362659B (en) * | 2018-02-07 | 2021-03-30 | 武汉轻工大学 | Edible oil type rapid identification method based on multi-source spectrum parallel fusion |
| CN109540838A (en) * | 2019-01-24 | 2019-03-29 | 广东产品质量监督检验研究院（国家质量技术监督局广州电气安全检验所、广东省试验认证研究院、华安实验室） | A kind of method of acidity in quick detection acidified milk |
| CN109540838B (en) * | 2019-01-24 | 2021-03-30 | 广东产品质量监督检验研究院（国家质量技术监督局广州电气安全检验所、广东省试验认证研究院、华安实验室） | Method for rapidly detecting acidity in fermented milk |
| CN116559386A (en) * | 2023-05-22 | 2023-08-08 | 淮阴工学院 | Milk freshness detection method based on dielectric spectrum |
| CN116559386B (en) * | 2023-05-22 | 2024-03-26 | 淮阴工学院 | Milk freshness detection method based on dielectric spectrum |
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