CN105527236A - Method for determination of main nutritional components of agricultural product by use of spectroscopy method - Google Patents
Method for determination of main nutritional components of agricultural product by use of spectroscopy method Download PDFInfo
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- 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
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- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
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Abstract
The present invention discloses a method for determination of main nutritional components of an agricultural product by use of spectroscopy method, the method is as follows: determining main nutritional components for determination by the spectroscopy method; determining the spectral range for determination of the main nutritional components of the agricultural product to be 800-2500nm; establishing a data model between spectrum and chemical components; and running a server to match K formulas in the data model according to name and nutritional components of the to-be-tested product, and computing to obtain the content of selected nutritional components of the tested agricultural product.
Description
Technical field
The invention belongs to material detection field, particularly relate to the method utilizing spectral detection chemical composition, specifically relate to a kind of method utilizing spectrographic determination agricultural product main nutrient composition.
Background technology
Along with the attention rate of people to food security is more and more higher, consumer is also more and more higher to the requirement of its Internal quality index when selecting agricultural product, the height of agricultural product nutritional labeling quality is usually used as the Primary Reference index selecting agricultural product, and the current mensuration to agricultural product nutritional labeling is often based on destructive chemical analysis or the experimental apparatus analysis using costliness in laboratory, these methods all need agricultural product to damage, and can not carry out Site Test Analysis.
CN102749370B discloses a kind of shell agricultural products index of quality and can't harm the method detected fast.By shell agricultural products surface impurity elimination to be detected, clean, select the intact unabroken modeling of shell shell agricultural products to be detected and the unknown shell agricultural products to be detected, be put in closed container, Electronic Nose is utilized to detect headspace gas, obtain sensor response, modeling is peeled off with shell agricultural products to be detected get core immediately, extract the mensuration that grease carries out acid value and peroxide value; Set up Electronic Nose response signal and the regression model of modeling between shell agricultural products acid value to be detected and peroxide value, select model that coefficient R value is large as the forecast model of shell agricultural products quality, the sensor response of shell agricultural products to be detected for the unknown is substituted into forecast model, evaluates its inside quality.
Above-mentioned patent is not analyzed the content of each Middle nutrition composition of agricultural product inside.Utilize spectral technique analysis to become the developing direction of crops composition detection at present, NIR spectra analysis analysis speed is fast, is because spectral measurement speed is very fast, the reason that calculation by computer speed is also very fast.And utilize near-infrared spectrum technique in the technology analyzing nutritional labeling, the foundation of its spectroscopic data model carries out according to the pattern of collection of illustrative plates, or to carry out according to local data, or match spectrum data are carried out on stoichiometric basis, after these methods all exist modeling, adjustment difficulty is large, basic data is incomplete, cause the correction of data model and the renewal of formula and change difficulty large, how to set up research emphasis and difficult point that spectroscopic data and agricultural product chemical composition data model become this field.
Summary of the invention
In order to overcome the various defects existing for said determination method, the invention provides a kind of method utilizing spectrographic determination agricultural product main nutrient composition, the method comprises the steps:
A. determine that spectrographic determination agricultural product main nutrient composition kind is T, T≤20;
B. determine that the spectral range that agricultural product main nutrient composition is measured is: 800-2500nm;
C. the spectroscopic data carrying out being more than or equal to more than 50 agricultural samples is collected and chemical detection Data Collection;
D. spectroscopic data and chemical detection data are utilized to set up data model, data model embedding data calculation server;
E. carry out spectroscopic data collection for agricultural product to be checked, spectroscopic data is inputted data operation server, select to need to detect agricultural product and nutritional labeling simultaneously, described nutritional labeling is one or more in the nutritional labeling determined in steps A;
F. calculation server is according to K formula in the name of product of required detection and nutritional labeling matched data model, carries out computing, obtain detect agricultural product the nutrient composition content selected, K >=T.
Described step D utilizes spectroscopic data and chemical detection data to set up data model, comprise the spectroscopic data input spectrum database of object, by the input chemline of the chemical detection data of same object, then the spectroscopic data in spectra database and the chemical detection data in chemline are mapped, form the mapping database of this object, comprise the steps:
Step I: the device launch spot launching spectral collection of holding concurrently with light source irradiates agricultural samples A1 to be detected, and collect the spectrum that agricultural samples A1 reflects, adopt spectral analysis apparatus to determine wavelength and the absorbance of collected spectrum, form the spectroscopic data of agricultural samples A1;
Step II: to agricultural samples A
1carry out chemical analysis, analyze content of starch, form the chemical detection data of agricultural samples;
Step II I: by agricultural product A
1spectroscopic data and the same database of chemical detection data inputting, form data-mapping X1;
Step IV: repeat above-mentioned steps I, Step II and Step II I, to agricultural samples A
2to A
n+1carry out n time to repeat, form n group spectroscopic data and corresponding n group chemical detection data, by spectroscopic data and the same database of chemical detection data inputting, form the data-mapping set of n group data-mapping;
Step V: the absorption values spectroscopic data in data-mapping set in above-mentioned database being chosen 2-100 wavelength carries out corresponding with chemical detection data, determines that 2-100 wavelength absorbance change and chemical detection data variation have K formula of quantitative and qualitative analysis relation.
Step VI: the K of above-mentioned steps formula is embedded calculation server, gathers agricultural product fresh sample A
xspectroscopic data, while its input database, 2-100 the wavelength typing calculation server that selecting step V determines, calculate the agricultural product fresh sample chemical data not carrying out actual detection, this chemical data is outputted to display end and database simultaneously, and in a database with agricultural product fresh sample A
xspectroscopic data formed measurement data map, this measurement data map with existing data-mapping form the data-mapping set upgraded.
Step VII: K formula on the database formed according to step I to step VI and calculation server, database is connected with calculation server, simultaneously the data input pin in setting data storehouse and data output end, the data input pin arranging calculation server and data output end, form the spectroscopic data model of agricultural product.
The method of data-mapping set is set up specifically in above-mentioned steps IV:
1) in spectroscopic data input spectrum database, data strip is set up according to nanoscale, each nanoscale wavelength is defined as a data strip, by in each nanoscale wavelength data and Wavelength strength data inputting database, form the spectroscopic data bar in spectra database, the nano wave length quantity k correspondence in spectral range forms the spectroscopic data bar k of respective numbers; Such as wavelength coverage is 1000-1500 nanometer, then have 501 spectroscopic data bars, and k is 501, and each spectroscopic data bar comprises wavelength and intensity;
2) in chemical detection data input chemline, chemical detection data are set up data strip by the quantity of detected composition, data strip is set up according to composition, each composition is defined as a data strip, by in each Components Name and component content input database, form the compositional data bar in chemline, the quantity correspondence of composition forms the compositional data bar of respective numbers; Such as, there is composition in 5 in the chemical detection data of object, then have 5 data strips, be respectively Y1, Y2 ... Y5, each data strip comprises Components Name and component content; Or chemical detection data are carried out permutation and combination, then using all permutation and combination as data strip data database, permutation and combination;
3) by all the components data strip in corresponding for the spectroscopic data bar of in spectral catalogue chemical data table, form mapping (enum) data group, the principle of correspondence is spectroscopic data bar corresponding each compositional data bar respectively, forms single spectrum and mapping (enum) data group corresponding to multicomponent; Such as spectroscopic data bar is X1000, and compositional data bar is Y1, Y2, Y3, Y4, Y5, be then { X1000Y1, X1000Y2, X1000Y3, X1000Y4, X1000Y5} for the single spectrum of 1000 nanometers and mapping (enum) data group corresponding to multicomponent;
According to the above-mentioned method setting up mapping (enum) data group, it is corresponding all spectroscopic data bars in spectral catalogue and all the components data strip in chemical data table to be carried out difference, forms the set of all mapping (enum) data groups, is mapping (enum) data set; Such as spectroscopic data bar is 501, compositional data bar is 5, comprise 501 × 5=2505 bar data in the mapping (enum) data set of the then spectroscopic data that formed of one-time detection and chemical detection data, these 2505 data are the mapping (enum) data set of object this detection.
If carry out n time to the different samples of this object to detect, then form n mapping (enum) data set, n mapping (enum) data set is unified in the independent database of input one, then form this object Mapping database.
Said n is more than or equal to 30, n and is more than or equal to 50, is more preferably, and n is more than or equal to 100.
Preferably, the wavelength coverage of described spectrum is 800-1800nm, or the wavelength coverage of spectrum is 1500-2500.
Preferably, described agricultural product are the substantially identical but same agricultural products of component content difference value within 20% of trophic component composition, without the need to pre-service or carry out incision and collect section process.
Preferably, the wavelength of 1001 wavelength and the data acquisition of intensity of described spectroscopic data to be wavelength be 800-1800nm, or the wavelength of 1001 wavelength and the data acquisition of intensity of spectroscopic data to be wavelength be 1500-2500.
Preferably, the number of described formula is K, and K value meets following relational expression:
T represents the nutritional labeling number of agricultural product, and wherein C represents knockdown implication
Preferably, described agricultural product comprise leaf vegetables, fruits, grain class, tubers, fruit vegetables.
Preferably, described nutritional labeling kind comprises starch, protein, sugar, fat, cellulose, glucose, tomatin, vitamin A, vitamin B3, vitamin C, Cobastab, malic acid, pectin, carrotene, folic acid.
In method of the present invention, chemical measurement data, also referred to as stoichiometry data, refer to the chemical data carrying out measuring acquisition by the national standard of Cucumber.Such as, content of starch in agricultural product, needs to measure according to national standard or industry standard, the instrument meeting GB measuring accuracy also can be adopted to measure.
In method of the present invention, spectroscopic data is the luminous energy of the different wave length collected by spectral collection device, and be converted into spectroscopic data by light inverted signal device, spectroscopic data General Requirements has spectral intensity, even if certain wavelength light intensity of wave is zero, then also need to record at spectroscopic data.
The beneficial effect of the inventive method is embodied in following three aspects:
1, when the present invention detects, agricultural samples, without the need to pre-service, reaches the effect of nondestructive measurement;
2, adopt spectral technique analysis to measure, analysis speed is fast, can detect at any time, convenient and swift;
3, the mapping method of spectroscopic data of the present invention and chemical detection data takes into full account the characteristic of single substance characteristics and the combination material detecting data, can the single nutritional labeling of Simultaneously test agricultural product or Multiple components as required;
4, the modeling method between spectroscopic data provided by the invention and chemical composition data conveniently can upgrade basic database, provides large and reliable data, improves and detects degree of accuracy, reduces personal error.
Embodiment
Embodiment 1
Utilize a method for spectrographic determination potato main nutrient composition, the method comprises the steps:
A. determine that spectrographic determination potato main nutrient composition is: starch, protein, sugar, fat, kind quantity is T=4;
B. determine that the spectral range that potato main nutrient composition is measured is: 800-2500nm;
C. the spectroscopic data carrying out 500 potato samples is collected and chemical detection Data Collection;
D. spectroscopic data and chemical detection data are utilized to set up data model, data model embedding data calculation server;
E. carry out spectroscopic data collection for potato to be checked, spectroscopic data is inputted data operation server, select the product that needs to detect and nutritional labeling, described nutritional labeling is one or more in the nutritional labeling determined in steps A simultaneously;
F. calculation server is according to 15 formula in the name of product of required detection and nutritional labeling matched data model, carries out computing, obtain detect potato the nutrient composition content selected.
Embodiment 2
Utilize a method for spectrographic determination watermelon main nutrient composition, the method comprises the steps:
A. determine that spectrographic determination watermelon main nutrient composition is: glucose, malic acid, tomatin, vitamin A, vitamin C, nutritional labeling kind quantity T=5;
B. determine that the spectral range that watermelon main nutrient composition is measured is: 700-2500nm;
C. the spectroscopic data carrying out 100 watermelon samples is collected and chemical detection Data Collection;
D. spectroscopic data and chemical detection data are utilized to set up data model, data model embedding data calculation server;
E. carry out spectroscopic data collection for watermelon to be checked, spectroscopic data is inputted data operation server, select the watermelon that needs to detect and nutritional labeling, described nutritional labeling is one or more in the nutritional labeling determined in steps A simultaneously;
F. calculation server is according to 21 formula in the name of product of required detection and nutritional labeling matched data model, carries out computing, obtain detect watermelon the nutrient composition content selected.
Embodiment 3
Utilize a method for spectrographic determination dragon fruit main nutrient composition, the method comprises the steps:
A. determine that spectrographic determination dragon fruit main nutrient composition is: protein, sugar, cellulose, vitamin A, vitamin B3, vitamin C, nutritional labeling kind quantity T=6;
B. determine that the spectral range that dragon fruit main nutrient composition is measured is: 800-2500nm;
C. the spectroscopic data carrying out 100 dragon fruit samples is collected and chemical detection Data Collection;
D. spectroscopic data and chemical detection data are utilized to set up data model, data model embedding data calculation server;
E. carry out spectroscopic data collection for dragon fruit to be checked, spectroscopic data is inputted data operation server, select the dragon fruit that needs to detect and nutritional labeling, described nutritional labeling is one or more in the nutritional labeling determined in steps A simultaneously;
F. calculation server is according to 63 formula in the name of product of required detection and nutritional labeling matched data model, carries out computing, obtain detect dragon fruit the nutrient composition content selected.
Embodiment 4
Utilize a method for spectrographic determination apple main nutrient composition, the method comprises the steps:
A. determine that spectrographic determination apple main nutrient composition is: sugar, malic acid, pectin, vitamin A, vitamin C, cellulose, nutritional labeling kind quantity T=6;
B. determine that the spectral range that apple main nutrient composition is measured is: 800-2500nm;
C. the spectroscopic data carrying out 100 apple samples is collected and chemical detection Data Collection;
D. spectroscopic data and chemical detection data are utilized to set up data model, data model embedding data calculation server;
E. carry out spectroscopic data collection for apple to be checked, spectroscopic data is inputted data operation server, select the product that needs to detect and nutritional labeling, described nutritional labeling is one or more in the nutritional labeling determined in steps A simultaneously;
F. calculation server is according to 63 formula in the name of product of required detection and nutritional labeling matched data model, carries out computing, obtain detect apple the nutrient composition content selected.
Embodiment 5
Utilize a method for spectrographic determination leaf vegetables main nutrient composition, the method comprises the steps:
A. determine that spectrographic determination leaf vegetables main nutrient composition is: vitamin C, Cobastab, carrotene, folic acid, cellulose, nutritional labeling kind quantity T=5;
B. determine that the spectral range that leaf vegetables main nutrient composition is measured is: 800-2500nm;
C. the spectroscopic data carrying out 100 leaf vegetables samples is collected and chemical detection Data Collection;
D. spectroscopic data and chemical detection data are utilized to set up data model, data model embedding data calculation server;
E. carry out spectroscopic data collection for leaf vegetables to be checked, spectroscopic data is inputted data operation server, select the product that needs to detect and nutritional labeling, described nutritional labeling is one or more in the nutritional labeling determined in steps A simultaneously;
F. calculation server is according to 21 formula in the name of product of required detection and nutritional labeling matched data model, carries out computing, obtain detect leaf vegetables the nutrient composition content selected, K >=T.
Embodiment 6
Utilize a method for spectrographic determination paddy rice main nutrient composition, the method comprises the steps:
A. determine that spectrographic determination paddy rice main nutrient composition is: starch, protein, fat, cellulose, nutritional labeling kind quantity T=4;
B. determine that the spectral range that paddy rice main nutrient composition is measured is: 800-2500nm;
C. the spectroscopic data carrying out 100 paddy rice samples is collected and chemical detection Data Collection;
D. spectroscopic data and chemical detection data are utilized to set up data model, data model embedding data calculation server;
E. carry out spectroscopic data collection for paddy rice to be checked, spectroscopic data is inputted data operation server, select the product that needs to detect and nutritional labeling, described nutritional labeling is one or more in the nutritional labeling determined in steps A simultaneously;
F. calculation server is according to 15 formula in the name of product of required detection and nutritional labeling matched data model, carries out computing, obtain detect paddy rice the nutrient composition content selected.
Claims (9)
1. utilize a method for spectrographic determination agricultural product main nutrient composition, the method comprises the steps:
A. determine that spectrographic determination agricultural product main nutrient composition kind quantity is T, T≤20;
B. determine that the spectral range that agricultural product main nutrient composition is measured is: 800-2500nm;
C. the spectroscopic data carrying out being more than or equal to n above agricultural samples is collected and chemical detection Data Collection, and wherein n is more than or equal to 50;
D. spectroscopic data and chemical detection data are utilized to set up the data model of K formula composition detection of agricultural products, data model embedding data calculation server;
E. carry out spectroscopic data collection for agricultural product to be checked, spectroscopic data is inputted data operation server, select the agricultural samples that needs to detect and nutritional labeling, described nutritional labeling is one or more in the nutritional labeling determined in steps A simultaneously;
F. calculation server is according to K formula in the name of product of required detection and nutritional labeling matched data model, carries out computing, obtain detect agricultural product the nutrient composition content selected, K >=T.
2. method according to claim 1, is characterized in that K value meets following relational expression:
T represents the nutritional labeling number of agricultural product, and wherein C represents knockdown implication.
3. method according to claim 1, is characterized in that, the wavelength coverage of described spectrum is 800-1800nm, or the wavelength coverage of spectrum is 1500-2500nm.
4. the method according to any one of claim 1-3, it is characterized in that, described agricultural product are the substantially identical but same agricultural products of component content difference value within 20% of trophic component composition, and agricultural samples is without the need to pre-service or carry out incision and collect section process.
5. method according to claim 1, is characterized in that n is more than or equal to 100, and preferred n is more than or equal to 200.
6. method according to claim 1, is characterized in that, the method that described step D data model is set up comprises the steps:
Step I: the device launch spot launching spectral collection of holding concurrently with light source irradiates agricultural samples A to be detected
1, and collect agricultural samples A
1the spectrum reflected, adopts spectral analysis apparatus to determine wavelength and the absorbance of collected spectrum, forms agricultural samples A
1spectroscopic data;
Step II: to agricultural samples A
1carry out chemical analysis, analyze its T kind composition and content, form the chemical detection data of agricultural samples;
Step II I: by agricultural product A
1spectroscopic data and the same database of chemical detection data inputting, form data-mapping X1;
Step IV: repeat above-mentioned steps I, Step II and Step II I, to agricultural samples A
2to A
n+1carry out n time to repeat, form n group spectroscopic data and corresponding n group chemical detection data, by spectroscopic data and the same database of chemical detection data inputting, form the data-mapping set of n group data-mapping;
Step V: the absorption values spectroscopic data in data-mapping set in above-mentioned database being chosen 2-100 wavelength carries out corresponding with chemical detection data, determines that 2-100 wavelength absorbance change and chemical detection data variation have K formula of quantitative and qualitative analysis relation;
Step VI: the K of above-mentioned steps formula is embedded calculation server, gathers agricultural product fresh sample A
xspectroscopic data, while its input database, 2-100 the wavelength typing calculation server that selecting step V determines, calculate the agricultural product fresh sample chemical data not carrying out actual detection, this chemical data is outputted to display end and database simultaneously, and in a database with agricultural product fresh sample A
xspectroscopic data formed measurement data map, this measurement data map with existing data-mapping form the data-mapping set upgraded.
Step VII: K formula on the database formed according to step I to step VI and calculation server, database is connected with calculation server, simultaneously the data input pin in setting data storehouse and data output end, the data input pin arranging calculation server and data output end, form the spectroscopic data model of agricultural product.
7. method according to claim 6, it is characterized in that, the wavelength of 1001 wavelength and the data acquisition of intensity of described spectroscopic data to be wavelength be 800-1800nm, or the wavelength of 1001 wavelength and the data acquisition of intensity of spectroscopic data to be wavelength be 1500-2500.
8. method according to claim 1, is characterized in that, agricultural product comprise leaf vegetables, fruits, grain class, tubers, fruit vegetables.
9. method according to claim 1, it is characterized in that, described nutritional labeling kind comprises starch, protein, sugar, fat, cellulose, glucose, tomatin, vitamin A, vitamin B3, vitamin C, Cobastab, malic acid, pectin, carrotene, folic acid.
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| CN113447450A (en) * | 2021-05-11 | 2021-09-28 | 中国农业科学院农产品加工研究所 | Optical nondestructive testing device for determining nutrient content of dishes based on spectrum |
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| CN113447450A (en) * | 2021-05-11 | 2021-09-28 | 中国农业科学院农产品加工研究所 | Optical nondestructive testing device for determining nutrient content of dishes based on spectrum |
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Application publication date: 20160427 |