CN103344597B - Anti-flavored-interference near infrared non-destructive testing method for internal components of lotus roots - Google Patents
Anti-flavored-interference near infrared non-destructive testing method for internal components of lotus roots Download PDFInfo
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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
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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
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
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Abstract
The invention provides an anti-flavored-interference near infrared non-destructive testing method for internal components of lotus roots, belonging to the technical field of the near infrared non-destructive testing. The invention comprises collecting lotus root samples flavored by salt or sugar with different concentrations, collecting near-infrared spectral information and physical data of the internal components of the samples, pre-treating spectrum data, building a near infrared spectroscopy model under a background of the salt or the sugar with the different concentrations by using a partial least squares method, performing correlation analysis and univariate regression analysis for the near infrared spectroscopy of salt or sugar content and the internal components of the lotus roots, correcting interferences of changes of the salt or sugar concentrations on the near infrared non-destructive testing for the internal components of the lotus roots, and finally building a near infrared spectroscopy model for the internal components of the flavored lotus roots on a basis of the near infrared spectroscopy model under the background of the salt or sugar with the different concentrations, wherein the model of the flavored lotus roots is adapt to changes in the concentrations of the salt or the sugar. The method effectively corrects interferences of changes of the salt or sugar concentrations on the near infrared non-destructive testing for the internal components of the lotus roots, and realizes rapid, accurate and real-time nondestructive test for the internal components of the lotus roots flavored by the salt or the sugar with different concentrations.
Description
Technical field
A method for the lotus rhizome internal component near infrared Non-Destructive Testing of anti-seasoning interference, relates to the method utilizing near-infrared spectrum technique to carry out the Non-Destructive Testing of seasoning lotus rhizome internal component particularly.Belong near infrared technical field of nondestructive testing.
Background technology
Lotus rhizome is the perennial large-scale aquatic herbaceous plant of Nymphaeceae Nelumbo, is the characteristic aquatic vegetable of China.Along with going deep into further of reform and opening-up, the lotus rhizome cultivated area of China constantly expands, more than 300,000 mu are reached at present, mainly be distributed in the Yangtze river basin and on the south each province, wherein especially concentrated with surrounding area distributions such as Taihu Lake, Hongchehu Lake, Dongting Lake, Poyang Lakes, gross annual output amount reaches more than 2,000,000 tons.The nutritional labeling of lotus rhizome is extremely abundant, starch-containing, robust fibre, protein, carrotene, thiamine, lactochrome, the mineral matter such as niacin and calcium, phosphorus, iron, it can be edible and medicinal, has the functions such as heat-clearing, relieving summer-heat, treatment diarrhoea, dysentery and dizziness.At present the processing of lotus rhizome product is developed, exporting goods and earning foreign currency increases dynamics, successively develop more than ten serial more or less a hundred converted products such as salt marsh, fresh-keeping, quick-frozen, poach, lotus root juice beverage, lotus root starch product, fast food mixing dish, the market demand of seasoned food that wherein sugaring, salt adding etc. process increases day by day.
Lotus rhizome is subject to the factor impacts such as artificial and nature in growth course, and individual difference is larger; In processing processing procedure, through variable concentrations seasoning, quality discrepancy is larger.In order to ensure the integrated quality of seasoning lotus rhizome, the differentiation based on surfaces such as color and luster, shape and sizes is far from being enough, and the detection carrying out seasoning lotus rhizome internal component is very important.At present at home, the means backwardness relatively that fruit-vegetable quality detects, the overwhelming majority rests on carries out by artificial sense primitive stage of identifying, this subjective assessment method is by the impact of personal experience, the color condition such as rate, mood, degree of fatigue and light respectively, in operating process, labor capacity is large, production efficiency is low, error is larger, and great majority rest on qualitative discrimination, its subjectivity, accuracy are poor, this causes the second-rate of China's export product to a great extent, very different, lack competitiveness in the international market.Another part then relies on analytical chemistry method to detect, and makes the integrality and the edibility that need destruction fruits and vegetables in this way, comparatively complicated, wastes time and energy, and is difficult to realize quick, pollution-free and harmlessization detection.The present invention adopts near infrared Dynamic Non-Destruction Measurement method effectively can overcome the deficiency of existing conventional sense existence, realize the synchro measure of the important indicators such as the starch of variable concentrations seasoning lotus rhizome, robust fibre and protein, have fast, non-destructive, without reagent analysis, safety, efficiently, the feature such as low cost and Simultaneously test various ingredients, to operation instruction, the quality grading of fruits and vegetables, and reduce sampling waste etc. all there is very high using value.
Current near-infrared spectral analysis technology is more at the quality Non-Destructive Testing application report of fruit, and in correlative study at home, Liu Yande (2005, Zhejiang University Ph.D. Dissertation) have studied the pol of fruit and the near infrared lossless detection method of acidity.Li Xin (2007, Agricultural University Of Shenyang's Master's thesis) have studied the method utilizing near infrared technology Non-Destructive Testing apple pear quality, relate to the index of quality such as soluble solid and total reducing sugar, acidity, vitamin C, water cut and single fruit weight of apple pear.Xia Junfang etc. (2007) utilize near infrared spectrum Accurate Prediction oranges and tangerines Vitamin C content.Cao Xia etc. (2013) apply near-infrared diffuse reflection spectrum technology Non-Destructive Testing mango pol.But the report of this technology in vegetables is few, relevant report both at home and abroad about the Non-Destructive Testing of lotus rhizome internal component near infrared only has one section, and Zhang Yongjun etc. (2008) have studied the near-infrared spectroscopy of the compositions such as lotus rhizome moisture, pol, robust fibre and hardness.The present invention with it unlike, the object of research is not fresh feed, but processing process seasoning lotus rhizome.The different salt of primary study of the present invention or sugared concentration seasoning on the impact of the near infrared spectrum Non-Destructive Testing of lotus rhizome internal component, and propose disposal route.
About the research that component concentration difference affects the near infrared Non-Destructive Testing of sample, current domestic report is less.Li Yong etc. (2005) have studied the impact of moisture difference on the robustness of NIR Spectroscopy Analysis Model, respectively from Pretreated spectra, valid interval choose and theoretical analysis has been carried out in three aspects such as overall calibration model, do not carry out the correction of model.The moisture that Zhang Lingshuai etc. (2005) analyze three different gradients measures the impact of Protein Content in Wheat near infrared, and when showing that near infrared measures Protein Content in Wheat, testing sample should keep suitable moisture.But do not study the relation of component concentration and the model scope of application.The present invention with it unlike, first analyze the near-infrared spectroscopy under different salt or sugared concentration background, again by correlation analysis and the single argument regretional analysis of the near infrared spectrum to salt or sugared content and lotus rhizome internal component, correction salt or sugared concentration change, to the interference of the near infrared Non-Destructive Testing of lotus rhizome internal component, finally establish the NIR Spectroscopy Analysis Model of the seasoning lotus rhizome internal component adapting to salinity or sugared concentration change.
Summary of the invention
The object of the invention is to overcome the deficiency that existing conventional sense exists in flavored fruit-vegetable context of detection, with the near-infrared analysis model that different salinity or sugared concentration are each concentration gradient of background constructing, and correlation analysis and single argument regretional analysis have been carried out to the near infrared spectrum of salt or sugared content and lotus rhizome internal component, determine the quantitative relationship of the predicted value increment of salt or sugared concentration and lotus rhizome internal component, then correction salt or sugared concentration change are to the interference of near infrared Non-Destructive Testing, finally establish the NIR Spectroscopy Analysis Model of the seasoning lotus rhizome internal component adapting to salinity or sugared concentration change.The invention provides one utilizes near-infrared spectrum technique to carry out seasoning lotus rhizome internal component lossless detection method, and it can realize harmlessization and detect, and easy and simple to handle, practicality is good, and reliability is high.
Technical scheme of the present invention: a kind of method of lotus rhizome internal component near infrared Non-Destructive Testing of anti-seasoning interference, gathers the lotus rhizome sample sets through different salinity or sugared concentration seasoning; Then the near infrared light spectrum information of collected specimens and the physicochemical data reference value of internal component; Spectroscopic data pre-service; Rear employing partial least square method sets up the near infrared spectrum calibration model under its variable concentrations gradient background; Correlation analysis is carried out to the near infrared spectrum of salt or sugared content and lotus rhizome internal component and overall calibration model is set up in single argument regretional analysis; Correction salt or sugared concentration change, to the interference of the near infrared Non-Destructive Testing of lotus rhizome internal component, the basis of the near-infrared spectroscopy finally under variable concentrations gradient background are set up the NIR Spectroscopy Analysis Model of the seasoning lotus rhizome internal component adapting to salinity or sugared concentration change; By this model, the near infrared light spectrum information of testing sample is converted to the parameter of seasoning lotus rhizome internal component to be measured, realizes the Non-Destructive Testing of seasoning lotus rhizome internal component; Step is:
(1) preparation of sample sets: gather non-seasoning and 5%, 10%, 15%, the lotus rhizome sample of 20% salinity or sugared concentration seasoning, choose calibration set and forecast set needed for the modeling of background with different salt adding or sugaring concentration respectively, wherein the quantitative proportion of calibration set and forecast set is 4:1; By as a control group unforseen, seasoning as experimental group;
(2) near infrared spectra collection of sample: use near infrared spectroscopy instrument to carry out spectra collection to the seasoning lotus rhizome sample that step (1) obtains, adopt diffuse reflection absorption spectroscopy, test parameters is set to: sweep limit is 4000 ~ 10000cm
-1, resolution is 8cm
-1, scanning times is 16 times; During near-infrared spectral measurement, complete one section of lotus rhizome is totally placed in diffuse reflection probe reposefully, each sample need carry out 4 spectral measurements, lay respectively at 4 relative positions at maximum gauge place, avoid obvious scratch, scar class surface imperfection as far as possible, during 4 times are measured, spectrum is averaged, and obtains the averaged spectrum of every section of lotus rhizome;
(3) mensuration of sample interior composition physicochemical data reference value: after calibration set and forecast set sample carry out spectra collection, as early as possible it is carried out to the mensuration of the reference value of internal component, result all represents with butt.Content of starch measures with reference to the GB/T5009.9-2008 mensuration of starch " in the food "-acid-hydrolysis method; Crude fiber content measures with reference to GB/T5009.10-2003 " in plant food coarse-fibred mensuration "; Protein content is with reference to GB/T5009.5-2010 " mensuration of Protein in Food ";
(4) pre-service of spectroscopic data: near infrared spectra collection and process are realized by TQ Analyst, pretreated method have the conversion of centralization, canonical variable, additional dispersion correction, Orthogonal Signal Correction Analyze, smoothly, Wavelet Denoising Method, differentiate change and genetic algorithm Wavelength optimization; Adopt which kind of preprocess method or will select according to the concrete condition of the quality of spectrum and background interference the need of pre-service, when using the preprocess method of spectrum, can be being used alone of a certain method of said method, also can be combinationally using of above-mentioned several method; By repeatedly optimizing calculating, obtain the modeling optimization parameter of different salt or sugared concentration seasoning lotus rhizome internal component;
(5) foundation of the near infrared spectrum calibration model of variable concentrations gradient: in conjunction with the spectroscopic data quantitative test function of mating in TQ analyst spectral analysis software and Matlab software, adopt partial least square method to set up forecast model to the spectroscopic data of the sample of pretreated calibration set and forecast set and the reference value that measures the starch of the lotus rhizome obtained, robust fibre and protein component, and model is optimized; Coefficient R, the standard deviation RMSEC of calibration set sample and the measurement of concetration precision of the standard deviation RMSEP of forecast set sample to model is adopted to assess; Calibration model distinguishes called after Model1(0% from low to high according to salt or sugared concentration), Model2(mass concentration 5%), Model3(10%) and, Model4(15%), Model5(20%); The related coefficient of the calibration model under each concentration background is all greater than 0.9200, shows that estimated performance is better;
(6) foundation of overall calibration model: correlation analysis and single argument regretional analysis are carried out to the near infrared spectrum of salt or sugared concentration and lotus rhizome internal component, show that the near infrared spectrum of salt or sugared concentration and lotus rhizome internal component is negative correlation; Calculate the predicted value increment △ C of lotus rhizome internal component according to the model under each salt or sugared concentration background, set up salt or sugared concentration C
saltor C
sugarwith the quantitative relationship of the simple regression of the predicted value increment △ C of lotus rhizome internal component, then from model predication value, deduct this increment, thus correction salt or sugared content are to the interference of the near infrared Non-Destructive Testing of seasoning lotus rhizome internal component;
Wherein, the computing formula of △ C is:
Cei is the predicted value of experimental group i-th sample; Cci is the predicted value of control group i-th sample; N is the sample number under each concentration gradient background, and n is 20;
(7) foundation of NIR Spectroscopy Analysis Model: last on the basis of the calibration model of variable concentrations gradient, sets up the NIR Spectroscopy Analysis Model of the seasoning lotus rhizome internal component adapting to salt or sugared concentration change;
(8) mensuration of testing sample internal component: the near infrared spectrum of the pretreated testing sample through step (3) is updated to the predicted value obtaining testing sample internal component in the NIR Spectroscopy Analysis Model of step (7), by the quantitative relation formula computational prediction value increment in step (6), from predicted value, then deduct the predicted value that namely this increment obtains revising.
Described near infrared spectrum is 4000 ~ 10000cm
-1near infrared spectrum in wavelength coverage, gather near infrared light spectrum information by near-infrared diffuse reflectance technology, resolution is 8cm
-1.
Described lotus rhizome internal component is one or more in starch, robust fibre and protein equal size, all adopts National Standard Method to obtain reference value.
Preferably, the near infrared light spectrum information of described collection has carried out pre-service, and described pre-service is multiplicative scatter correction, differentiate conversion, eliminate the baseline wander of spectroscopic data or the impact of mild background interference, and carry out smoothing processing, Removing Random No, improve signal to noise ratio (S/N ratio).
Preferably, the near infrared spectrum of described salt or sugared content and lotus rhizome internal component has carried out correlation analysis and single argument regretional analysis, effectively have modified salt or sugared concentration change to the interference of near infrared Non-Destructive Testing.
Described near-infrared spectroscopy uses the spectroscopic data quantitative test function and Matlab software of mating in TQ analyst spectral analysis software, and adopt partial least square method founding mathematical models, model obtains after repeatedly optimizing.
Described seasoning is sugaring or salt adding seasoning, and its concentration range is 5% ~ 20%.
Beneficial effect of the present invention: compared with prior art, tool of the present invention has the following advantages:
1, sample is without the need to any process, can realize polycomponent and measure simultaneously.
2, apply existing Near-Infrared Spectroscopy Instruments, spectroscopic data through multiplicative scatter correction, differentiate and the process such as level and smooth, and has carried out correlation analysis and single argument regretional analysis, effectively have modified salt or sugared concentration change to the interference of near infrared Non-Destructive Testing.
3, the model set up is applicable to the near infrared Non-Destructive Testing of different salt or sugared concentration change.
Embodiment
The technological means realized to make the present invention, creation characteristic, reaching object and effect is easy to understand, below in conjunction with specific embodiment, setting forth the present invention further.Enforcement software and hardware of the present invention mainly contains the parts such as near infrared spectrometer, stoichiometry software and computing machine.Whole implementation process is described as follows:
The method of the lotus rhizome internal component near infrared Non-Destructive Testing of embodiment 1 salt adding seasoning
1, the preparation of sample sets.Gather non-seasoning and 5%, 10%, 15%, the lotus rhizome sample of 20% salinity seasoning, choose respectively with different salt content calibration set and forecast set needed for the modeling of background, wherein the quantitative proportion of calibration set and forecast set is about 4:1.By as a control group unforseen, other are as experimental group.
2, the spectra collection of sample.Near infrared spectroscopy instrument is used to carry out spectra collection to seasoning lotus rhizome sample obtained above.Adopt diffuse reflection absorption spectroscopy, test parameters is set to: sweep limit is 4000 ~ 10000cm
-1, resolution is 8cm
-1, scanning times is 16 times.During near-infrared spectral measurement, complete one section of lotus rhizome is totally placed in diffuse reflection probe reposefully, each sample need carry out 4 spectral measurements, lay respectively at 4 relative positions at maximum gauge place, avoid obvious surface imperfection (scratch, scar etc.) as far as possible, during 4 times are measured, spectrum is averaged, and makes the averaged spectrum obtaining every section of lotus rhizome.
3, the mensuration of samples Reference value.After calibration set and forecast set sample carry out spectra collection, just as early as possible it is carried out to the mensuration of the reference value of internal component, result all represents with butt.Content of starch measures with reference to the GB/T5009.9-2008 mensuration of starch " in the food "-acid-hydrolysis method; Crude fiber content measures with reference to GB/T5009.10-2003 " in plant food coarse-fibred mensuration "; Protein content is with reference to GB/T5009.5-2010 " mensuration of Protein in Food ".
4, the pre-service of spectroscopic data.Near infrared spectra collection and process are realized by TQ Analyst.In order to the impact of the baseline wander or mild background interference that reduce spectroscopic data, Removing Random No, improves signal to noise ratio (S/N ratio), and adjusting correlation parameter during Modling model and optimizing is one of Main Means improving model prediction ability and prediction effect.Pretreated method has the conversion of centralization, canonical variable, additional dispersion correction, Orthogonal Signal Correction Analyze, level and smooth, Wavelet Denoising Method, differentiate change and genetic algorithm Wavelength optimization etc.Adopt which kind of preprocess method or will select according to the concrete condition of the quality of spectrum and background interference the need of pre-service, when using the preprocess method of spectrum, can be being used alone of a certain method of said method, also can be combinationally using of above-mentioned several method.By repeatedly optimizing calculating, obtain the modeling optimization parameter of different salinity seasoning lotus rhizome internal component as table 1.
The modeling optimization parameter of table 1 different salinity seasoning lotus rhizome internal component
5, the foundation of the calibration model of different gradient.In conjunction with the spectroscopic data quantitative test function of mating in TQ analyst spectral analysis software and Matlab software, to the spectroscopic data of the sample of pretreated calibration set and forecast set with carry out the reference value employing partial least square method that said method measures the compositions such as the starch of the lotus rhizome obtained, robust fibre and protein and set up forecast model, and model is optimized.Related coefficient (R), the standard deviation (RMSEC) of calibration set sample and the measurement of concetration precision of standard deviation (RMSEP) to model of forecast set sample is adopted to assess.Calibration model is ordered as Model1(0% from low to high respectively according to salinity), Model2(5%), Model3(10%) and, Model4(15%), Model5(20%) and, it the results are shown in Table 2.The related coefficient of the calibration model under each concentration background is all greater than 0.9200, shows that estimated performance is better.Wherein the RMSEP of Model2 ~ 5 is less than the RMSEP of Model1, and this illustrates that the predictive ability of Model2 ~ 5 and precision are higher than Model1.This is because salt can not produce near ir absorption peaks, but the moisture that can change lotus rhizome is to the interference of near infrared Non-Destructive Testing, thus the near infrared Non-Destructive Testing of remote effect lotus rhizome internal component.
Calibration model under the different salinity background of table 2
6, the foundation of overall calibration model.Correlation analysis and single argument regretional analysis are carried out to the near infrared spectrum of salinity and lotus rhizome internal component, show that the near infrared spectrum of salinity and lotus rhizome internal component is negative correlation.Calculate the predicted value increment △ C of lotus rhizome internal component according to the model under each salinity background, the results are shown in Table 3.Set up salinity C
saltwith the quantitative relationship (see table 4) of the simple regression of the predicted value increment △ C of lotus rhizome internal component, then from model predication value, deduct this increment, thus revise the interference of salt content change to the near infrared Non-Destructive Testing of seasoning lotus rhizome internal component.Last on the basis of the calibration model of variable concentrations gradient, set up the NIR Spectroscopy Analysis Model (see table 2) of the seasoning lotus rhizome internal component adapting to salinity change.
Wherein, the computing formula of △ C is:
Cei is the predicted value of experimental group i-th sample; Cci is the predicted value of control group i-th sample; N is the sample number under each gradient background, and n is 20;
The predicted value increment of lotus rhizome internal component under the different salinity of table 3
| Starch concentration | Protein concentration | Robust fibre concentration |
| Prediction increment △ C | Prediction increment △ C | Prediction increment △ C | |
| Model1 | 0.0000 | 0.0000 | 0.0000 |
| Model2 | -0.1388 | -0.0255 | -0.0131 |
| Model3 | -0.2009 | -0.0351 | -0.0199 |
| Model4 | -0.3102 | -0.0503 | -0.0264 |
| Model5 | -0.3821 | -0.0628 | -0.0352 |
Table 4 salinity C
saltwith the quantitative relation formula of the predicted value increment △ C of lotus rhizome internal component
7, the mensuration of testing sample internal component.The predicted value obtaining testing sample internal component in the NIR Spectroscopy Analysis Model set up is updated to by through the near infrared spectrum as the pretreated testing sample of step 3, by quantitative relation formula (see table 4) the computational prediction value increment in step 6, from predicted value, then deduct the predicted value that namely this increment obtains revising.
The method of the lotus rhizome internal component near infrared Non-Destructive Testing of embodiment 2 sugaring seasoning
1, the preparation of sample sets.Gather non-seasoning and 5%, 10%, 15%, the lotus rhizome sample of 20% sugared concentration seasoning, other are with embodiment 1.
2, the spectra collection of sample.With embodiment 1.
3, the mensuration of samples Reference value.With embodiment 1.
4, the pre-service of spectroscopic data.With implementing 1.The modeling optimization parameter of different sugar concentration seasoning lotus rhizome internal component is as table 5.
The modeling optimization parameter of table 5 different sugar concentration seasoning lotus rhizome internal component
5, the foundation of the calibration model of different gradient.The modeling method adopted, with embodiment 1, the results are shown in Table 6.The related coefficient of the calibration model under each concentration background is all greater than 0.9100, shows that estimated performance is better.Wherein the RMSEP of Model2 ~ 5 is greater than the RMSEP of Model1, and this illustrates that the predictive ability of Model2 ~ 5 and precision will lower than Model1.This is because sugaring seasoning has made lotus rhizome many a kind of component having near ir absorption peaks, thus affect the near infrared Non-Destructive Testing of lotus rhizome internal component.
Calibration model under table 6 different sugar concentration background
6, the foundation of overall calibration model.Correlation analysis and single argument regretional analysis are carried out to the near infrared spectrum of sugared concentration and lotus rhizome internal component, draws the being proportionate property of near infrared spectrum of sugared concentration and lotus rhizome internal component.The calculating of predicted value increment △ C, with embodiment 1, the results are shown in Table 7.Set up sugared concentration C
sugarwith the quantitative relationship (see table 8) of the predicted value increment △ C of each composition, then from model predication value, deduct this increment, thus revise the interference of sugared content to the near infrared Non-Destructive Testing of seasoning lotus rhizome internal component.Last on the basis of the calibration model of variable concentrations gradient, set up the NIR Spectroscopy Analysis Model (see table 6) of the seasoning lotus rhizome internal component adapting to sugared concentration change.
The predicted value increment of lotus rhizome internal component under table 7 different sugar concentration
The sugared concentration C of table 8
sugarwith the quantitative relation formula of the predicted value increment △ C of lotus rhizome internal component
7, the mensuration of testing sample internal component.With embodiment 1.
Claims (1)
1. a method for the lotus rhizome internal component near infrared Non-Destructive Testing of anti-seasoning interference, is characterized in that the lotus rhizome sample sets gathered through different salinity or sugared concentration seasoning; Then the near infrared light spectrum information of collected specimens and the physicochemical data reference value of internal component; Spectroscopic data pre-service; Rear employing partial least square method sets up the near infrared spectrum calibration model under its variable concentrations gradient background; Correlation analysis is carried out to the near infrared spectrum of salt or sugared content and lotus rhizome internal component and overall calibration model is set up in single argument regretional analysis; Correction salt or sugared concentration change, to the interference of the near infrared Non-Destructive Testing of lotus rhizome internal component, the basis of the near-infrared spectroscopy finally under variable concentrations gradient background are set up the NIR Spectroscopy Analysis Model of the seasoning lotus rhizome internal component adapting to salinity or sugared concentration change; By this model, the near infrared light spectrum information of testing sample is converted to the parameter of seasoning lotus rhizome internal component to be measured, realizes the Non-Destructive Testing of seasoning lotus rhizome internal component; Step is:
(1) preparation of sample sets: gather non-seasoning and 5%, 10%, 15%, the lotus rhizome sample of 20% salinity or sugared concentration seasoning, choose calibration set and forecast set needed for the modeling of background with different salt adding or sugaring concentration respectively, wherein the quantitative proportion of calibration set and forecast set is 4:1; By as a control group unforseen, seasoning as experimental group;
(2) near infrared spectra collection of sample: use near infrared spectroscopy instrument to carry out spectra collection to the seasoning lotus rhizome sample that step (1) obtains, adopt diffuse reflection absorption spectroscopy, test parameters is set to: sweep limit is 4000 ~ 10000cm
-1, resolution is 8cm
-1, scanning times is 16 times; During near-infrared spectral measurement, complete one section of lotus rhizome is totally placed in diffuse reflection probe reposefully, each sample need carry out 4 spectral measurements, lay respectively at 4 relative positions at maximum gauge place, avoid obvious scratch, scar class surface imperfection as far as possible, during 4 times are measured, spectrum is averaged, and obtains the averaged spectrum of every section of lotus rhizome;
(3) mensuration of sample interior composition physicochemical data reference value: after calibration set and forecast set sample carry out spectra collection, as early as possible it is carried out to the mensuration of the reference value of internal component, result all represents with butt; Content of starch measures with reference to the GB/T5009.9-2008 mensuration of starch " in the food "-acid-hydrolysis method; Crude fiber content measures with reference to GB/T5009.10-2003 " in plant food coarse-fibred mensuration "; Protein content is with reference to GB/T5009.5-2010 " mensuration of Protein in Food ";
(4) pre-service of spectroscopic data: near infrared spectra collection and process are realized by TQ Analyst, pretreated method have the conversion of centralization, canonical variable, additional dispersion correction, Orthogonal Signal Correction Analyze, smoothly, Wavelet Denoising Method, differentiate change and genetic algorithm Wavelength optimization; Adopt which kind of preprocess method or will select according to the concrete condition of the quality of spectrum and background interference the need of pre-service, when using the preprocess method of spectroscopic data, being used alone of a certain method of said method, or the combinationally using of above-mentioned several method; By repeatedly optimizing calculating, obtain the modeling optimization parameter of different salt or sugared concentration seasoning lotus rhizome internal component;
(5) foundation of the near infrared spectrum calibration model of variable concentrations gradient: in conjunction with the spectroscopic data quantitative test function of mating in TQ analyst spectral analysis software and Matlab software, adopt partial least square method to set up calibration model to the spectroscopic data of the sample of pretreated calibration set and forecast set and the reference value that measures the starch of the lotus rhizome obtained, robust fibre and protein component, and model is optimized; Coefficient R, the standard deviation RMSEC of calibration set sample and the measurement of concetration precision of the standard deviation RMSEP of forecast set sample to model is adopted to assess; Calibration model is named from low to high respectively according to salt or sugared concentration: 0% is Model1, and 5% is Model2, and 10% is Model3, and 15% is Model4, and 20% is Model5; The related coefficient of the calibration model under each concentration background is all greater than 0.920, shows that estimated performance is better;
(6) foundation of overall calibration model: correlation analysis and single argument regretional analysis are carried out to the near infrared spectrum of salt or sugared concentration and lotus rhizome internal component, show that the near infrared spectrum of salt or sugared concentration and lotus rhizome internal component is negative correlation; Calculate the predicted value increment △ C of lotus rhizome internal component according to the model under each salt or sugared concentration background, set up salt or sugared concentration C
saltor C
sugarwith the quantitative relationship of the simple regression of the predicted value increment △ C of lotus rhizome internal component, then from model predication value, deduct this increment, thus correction salt or sugared content are to the interference of the near infrared Non-Destructive Testing of seasoning lotus rhizome internal component;
Wherein, the computing formula of △ C is: △ C=
cei is the predicted value of experimental group i-th sample; Cci is the predicted value of control group i-th sample; N is the sample number under each concentration gradient background, and n is 20;
(7) foundation of NIR Spectroscopy Analysis Model: last on the basis of the calibration model of variable concentrations gradient, sets up the NIR Spectroscopy Analysis Model of the seasoning lotus rhizome internal component adapting to salt or sugared concentration change;
(8) mensuration of testing sample internal component: the near infrared spectrum of the pretreated testing sample through step (3) is updated to the predicted value obtaining testing sample internal component in the NIR Spectroscopy Analysis Model of step (7), by the quantitative relation formula computational prediction value increment in step (6), from predicted value, then deduct the predicted value that namely this increment obtains revising.
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