CN104198529A - Method for distinguishing donkey-hide gelatin by utilizing electronic nose technology - Google Patents
Method for distinguishing donkey-hide gelatin by utilizing electronic nose technology Download PDFInfo
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- CN104198529A CN104198529A CN201410387156.XA CN201410387156A CN104198529A CN 104198529 A CN104198529 A CN 104198529A CN 201410387156 A CN201410387156 A CN 201410387156A CN 104198529 A CN104198529 A CN 104198529A
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Abstract
The invention discloses a method for distinguishing donkey-hide gelatin by utilizing an electronic nose technology. The method comprises the following steps of selecting a donkey-hide gelatin product of a designated factory as a sample; respectively detecting each specimen in the sample, crushing the specimens into powder, weighing the specimens of a given amount, placing the specimens into a sealed specimen bottle, stirring the specimens for a period of time, extracting partial gas in the specimen bottle and then injecting the gas into an electronic nose gas chamber, and collecting the specimen data by adopting a sensor array in the electronic nose gas chamber; classifying the specimen data in the sample into a correction set of data and a verification set of data, establishing a judgment model by adopting the correction set of data, and verifying the established judgment model through the verification set of data; collecting the specimen data of the to-be-detected donkey-hide gelatin sample, and calculating the distance from the main component data of the to-be-detected donkey-hide gelatin sample to the center of main components of a main component analysis model of a training set to obtain a value F of the to-be-detected donkey-hide gelatin sample, judging whether the precision has remarkable difference or not according to a confidence interval of a set homogeneity test of variance, and determining that the donkey-hide gelatin without remarkable difference is the donkey-hide gelatin of the designated factory.
Description
Technical field
The present invention relates to donkey-hide gelatin and differentiate field, in particular to a kind of method of utilizing Electronic Nose Technology to differentiate donkey-hide gelatin.
Background technology
Donkey-hide gelatin, the existing history in 3000 of its application, is always described as " panacea of enriching blood ", " nourishing national treasure ", is described as " Chinese medicine Triratna " together with ginseng, pilose antler.The original producton location of donkey-hide gelatin is Shandong " Donga County ".Donga donkey-hide gelatin always name hat, until almost become the synonym of donkey-hide gelatin today " Donga donkey-hide gelatin ", also develops into the abbreviation to the donkey-hide gelatin of largest domestic and series of products manufacturing enterprise-Dong-E donkey-hide Gelatin Co., Ltd., Shandong Prov. simultaneously all over the world.
At present, donkey-hide gelatin manufacturer is numerous, because raw material is different with production technology, cause product quality uneven, but standards of pharmacopoeia arrange relatively low at present, cannot judge true and false quality and the quality grade of donkey-hide gelatin, particularly some producers fill goodly in proper order, and second-rate donkey-hide gelatin is sold with the name of the donkey-hide gelatin of famous mark producer, destroy market order, cause the dysgenic while to the fame of famous mark producer, also cheat and injured consumer.Under this background, be badly in need of a kind of objective, method is identified donkey-hide gelatin product fast and effectively, so that consumer distinguishes the donkey-hide gelatin product of famous-brand and high-quality producer and the donkey-hide gelatin product of other manufacturers.
Summary of the invention
The invention provides a kind of method of utilizing Electronic Nose Technology to differentiate donkey-hide gelatin, in order to objective, quickly and efficiently donkey-hide gelatin product is identified, to distinguish the donkey-hide gelatin product of particular vendors and the donkey-hide gelatin product of other manufacturers.
For achieving the above object, the invention provides a kind of method of utilizing Electronic Nose Technology to differentiate donkey-hide gelatin, comprise the following steps:
A) the donkey-hide gelatin product of choosing particular vendors is as sample;
B) each sample in described sample is detected, testing process is:
B1) the broken end of sample after sample is pulverized and sieved takes 0.5-2.0g and is placed in the sealing specimen bottle that volume is 5-20ml, stirs 1000s-3000s, the gas in described specimen bottle is got to entry needle for 1-5ml and inject Electronic Nose air chamber; In described Electronic Nose air chamber, be provided with 3 chambers, described 3 chambers are provided with totally 18 sensor arraies that sensor forms;
B2) described sensor array gathers the sample data in described specimen bottle; Wherein, the sample data of each sample gathers 3 times, averages; The sample data gathering is the characteristic response spectrum of sample smell;
C) to all samples data in this sample, be divided into calibration set data and checking collection data, adopt described calibration set data to set up discrimination model, and by described checking collection data, set up discrimination model is verified;
The method that wherein adopts described calibration set data to set up discrimination model is:
C1) data of single sample are carried out to pre-service, characteristic information extraction also carries out following conversion:
Wherein, SNV
iit is the standard normal variable of i sensor response in the Electronic Nose signal of single sample; x
ibe the response of i sensor in this single sample;
the mean value of all the sensors response in the Electronic Nose signal of this single sample; P is the number of probes in Electronic Nose air chamber; I is natural number, and its span is from 1 to p;
C2) obtain all samples data after pretreatment in calibration set, adopt SIMCA method to principal component analysis (PCA) discrimination model of this Sample Establishing, first using the sample in described calibration set as a training set, the sample data matrix of described training set is carried out respectively to principal component analysis (PCA), set up the principal component analysis (PCA) discrimination model of described training set and with leaving-one method, described principal component analysis (PCA) discrimination model be optimized; Wherein said sample data matrix is comprised of the peak value of the response of p sensor;
D) according to the method for step b, gather the sample data of donkey-hide gelatin sample to be detected, and according to the method for step c1, the sample data of donkey-hide gelatin sample to be detected is carried out to pre-service, by principal component analysis (PCA) discrimination model described in the sample data substitution of donkey-hide gelatin sample to be detected, the number of principal components that obtains donkey-hide gelatin sample to be detected according to and the distance at the major component center of the principal component analysis (PCA) discrimination model of described training collection, and according to this apart from the F calculated value F that calculates the homogeneity test of variance of donkey-hide gelatin sample to be detected
calculate, according to the fiducial interval of the homogeneity test of variance classification of setting, by F
calculatecritical value F with the level of significance α place setting
criticalcompare, judge whether the precision of donkey-hide gelatin sample to be detected and described principal component analysis (PCA) discrimination model has significant difference, if F
calculate﹤ F
critical, there is not significant difference in the donkey-hide gelatin sample of donkey-hide gelatin sample to be detected and this particular vendors, regards as the donkey-hide gelatin that donkey-hide gelatin sample to be detected is this particular vendors, if F
meter calculate﹥ F
critical, there is significant difference in the donkey-hide gelatin sample of donkey-hide gelatin sample to be detected and this particular vendors, regards as the donkey-hide gelatin that donkey-hide gelatin sample to be detected is not this particular vendors.
Wherein, this sample that step is chosen in a) at least has 20 samples.
Wherein, described sensor array comprises strong oxidability gas sensor, toxic gas sensor, organic compound sensor, inflammable gas sensor and aromatics sensor.
Wherein, the temperature of described entry needle is 80 ℃-150 ℃, and injection speed is 1-5ml/s.
Wherein, to gather the acquisition time of the sample data in described specimen bottle be 60-600s to described sensor array.
Wherein, the speed that sample stirs in described specimen bottle is 300-900rpm.
Wherein, in described specimen bottle, to produce the temperature of gas be 50 ℃-150 ℃ to sample.
Wherein, the level of significance α of setting is 0.05.
Compared with prior art, beneficial effect of the present invention is embodied in:
The method of utilizing Electronic Nose Technology to differentiate donkey-hide gelatin provided by the invention, sensor by Electronic Nose responds, according to the standard normal variable of sample, set up discrimination model, and utilize F to check, objective, accurate, quick, analytic process is easy, and amount of samples is few, and extend to other field, there is very high practicality.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, to the accompanying drawing of required use in embodiment or description of the Prior Art be briefly described below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skills, do not paying under the prerequisite of creative work, can also obtain according to these accompanying drawings other accompanying drawing.
Fig. 1 is that the Electronic Nose Technology of utilizing of one embodiment of the invention is differentiated the method flow diagram of donkey-hide gelatin;
Fig. 2 be one embodiment of the invention utilize Electronic Nose Technology to differentiate Donga donkey-hide gelatin time sample data;
Fig. 3 be one embodiment of the invention utilize Electronic Nose Technology to differentiate Donga donkey-hide gelatin time the donkey-hide gelatin sample to be detected sample data that is adulterant donkey-hide gelatin;
Fig. 4 be one embodiment of the invention utilize Electronic Nose Technology to differentiate Donga donkey-hide gelatin time the donkey-hide gelatin sample to be detected sample data that is other brand donkey-hide gelatin.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is only the present invention's part embodiment, rather than whole embodiment.Embodiment based in the present invention, those of ordinary skills, not paying the every other embodiment obtaining under creative work prerequisite, belong to the scope of protection of the invention.
Fig. 1 is that the Electronic Nose Technology of utilizing of one embodiment of the invention is differentiated the method flow diagram of donkey-hide gelatin.As shown in Figure 1, a kind of method of utilizing Electronic Nose Technology to differentiate donkey-hide gelatin of the present invention, comprises the following steps:
A) the donkey-hide gelatin product of choosing particular vendors is as sample;
B) each sample in described sample is detected, testing process is:
B1) the broken end of sample after sample is pulverized and sieved takes 0.5-2.0g and is placed in the sealing specimen bottle that volume is 5-20ml, stirs 1000s-3000s, the gas in described specimen bottle is got to entry needle for 1-5ml and inject Electronic Nose air chamber; In described Electronic Nose air chamber, be provided with 3 chambers, described 3 chambers are provided with totally 18 sensor arraies that sensor forms;
B2) described sensor array gathers the sample data in described specimen bottle; Wherein, the sample data of each sample gathers 3 times, averages; The sample data gathering is the characteristic response spectrum of sample smell;
C) to all samples data in this sample, be divided into calibration set data and checking collection data, adopt described calibration set data to set up discrimination model, and by described checking collection data, set up discrimination model is verified;
The method that wherein adopts described calibration set data to set up discrimination model is:
C1) data of single sample are carried out to pre-service, characteristic information extraction also carries out following conversion:
Wherein, SNV
iit is the standard normal variable of i sensor response in the Electronic Nose signal of single sample; x
ibe the response of i sensor in this single sample;
the mean value of all the sensors response in the Electronic Nose signal of this single sample; P is the number of probes in Electronic Nose air chamber; I is natural number, and its span is from 1 to p;
C2) obtain all samples data after pretreatment in calibration set, adopt SIMCA method to principal component analysis (PCA) discrimination model of this Sample Establishing, first using the sample in described calibration set as a training set, the sample data matrix of described training set is carried out respectively to principal component analysis (PCA), set up the principal component analysis (PCA) discrimination model of described training set and with leaving-one method, described principal component analysis (PCA) discrimination model be optimized; Wherein said sample data matrix is comprised of the peak value of the response of p sensor;
D) according to the method for step b, gather the sample data of donkey-hide gelatin sample to be detected, and according to the method for step c1, the sample data of donkey-hide gelatin sample to be detected is carried out to pre-service, by principal component analysis (PCA) discrimination model described in the sample data substitution of donkey-hide gelatin sample to be detected, the number of principal components that obtains donkey-hide gelatin sample to be detected according to and the distance at the major component center of the principal component analysis (PCA) discrimination model of described training collection, and according to this apart from the F calculated value F that calculates the homogeneity test of variance of donkey-hide gelatin sample to be detected
calculate, according to the fiducial interval of the homogeneity test of variance classification of setting, by F
calculatecritical value F with the level of significance α place setting
criticalcompare, judge whether the precision of donkey-hide gelatin sample to be detected and described principal component analysis (PCA) discrimination model has significant difference, if F
calculate﹤ F
critical, there is not significant difference in the donkey-hide gelatin sample of donkey-hide gelatin sample to be detected and this particular vendors, regards as the donkey-hide gelatin that donkey-hide gelatin sample to be detected is this particular vendors, if F
meter calculate﹥ F
critical, there is significant difference in the donkey-hide gelatin sample of donkey-hide gelatin sample to be detected and this particular vendors, regards as the donkey-hide gelatin that donkey-hide gelatin sample to be detected is not this particular vendors.
In one embodiment of the invention, this sample that step is chosen in a) at least has 20 samples.
In one embodiment of the invention, described sensor array comprises strong oxidability gas sensor, toxic gas sensor, organic compound sensor, inflammable gas sensor and aromatics sensor.
In one embodiment of the invention, the temperature of described entry needle is 80 ℃-150 ℃, and injection speed is 1-5ml/s.
In one embodiment of the invention, to gather the acquisition time of the sample data in described specimen bottle be 60-600s to described sensor array.
In one embodiment of the invention, the speed that sample stirs in described specimen bottle is 300-900rpm.
In one embodiment of the invention, in described specimen bottle, to produce the temperature of gas be 50 ℃-150 ℃ to sample.
In one embodiment of the invention, the sample number ratio of described calibration set and described checking collection is about 2:1.
In one embodiment of the invention, the level of significance α of setting is 0.05.
Take below and differentiate that the donkey-hide gelatin product (hereinafter to be referred as Donga donkey-hide gelatin) that Dong-E donkey-hide Gelatin Co., Ltd., Shandong Prov. produces is example, illustrate implementation process of the present invention.
Choose Donga donkey-hide gelatin sample that 30 lot numbers are 120433 as sample;
Each Donga donkey-hide gelatin sample in described sample is detected, and testing process is:
B1) by Donga donkey-hide gelatin sample grinding and sieving, obtain the broken end of sample, the 1.0g taking in sample is placed in the sealing specimen bottle that volume is 10ml, at the temperature of 90 ℃, stirs 1800s, and agitation speed is 500rpm.Gas in described specimen bottle is got to 2.0ml and with entry needle, inject Electronic Nose air chamber; The temperature of entry needle is 100 ℃, and cumulative volume is 5.0ml, and injection speed is 2.0ml/s.In described Electronic Nose air chamber, be provided with 3 chambers, described 3 chambers are provided with totally 18 sensor arraies that sensor forms.Described sensor array comprises strong oxidability gas sensor, toxic gas sensor, organic compound sensor, inflammable gas sensor and aromatics sensor.In the present embodiment, what adopt is the FOX4000 Electronic Nose of French Alpha MOS company, be furnished with HS100 type automatic sampler, air compressor, air purifier, can select as required required operative sensor in 18 sensors, its gas effectively detecting please refer to table 1.
Sensor array and sensitive gas thereof in table 1 FOX4000 Electronic Nose
In the present embodiment, 18 sensors are all selected, and sensor array gathers the sample data in described specimen bottle; Wherein, the sample data of each sample gathers 3 times, and each acquisition time is 120s, averages; The sample data gathering is the characteristic response spectrum of Donga donkey-hide gelatin sample smell.The Donga donkey-hide gelatin sample data gathering in the present embodiment as shown in Figure 2.
Sample data to 30 samples in this sample, is divided into calibration set data and checking collection data, and using the peak value of response of 18 sensors as sample data matrix.Wherein, calibration set data comprise 20 Donga donkey-hide gelatin sample datas, and checking collection data comprise 10 Donga donkey-hide gelatin sample datas.Adopt described calibration set data to set up discrimination model, and by described checking collection data, set up discrimination model is verified.
The method that wherein adopts described calibration set data to set up discrimination model is:
The data of single sample are carried out to pre-service, and characteristic information extraction also carries out following conversion:
Wherein, SNV
iit is the standard normal variable of i sensing data in the Electronic Nose signal of single sample; x
ibe the response of i sensor in this sample;
the mean value of this single sample signal all the sensors response; 18 is the number of probes in Electronic Nose air chamber; I is natural number, and its span is from 1 to 18;
Obtain all samples data after pretreatment in calibration set, adopt SIMCA method to PCA discriminatory analysis model of this Sample Establishing, first using the sample in described calibration set as a training set, the sample data matrix of training set described in each is carried out respectively to principal component analysis (PCA), set up the principal component analysis (PCA) mathematical model of training set described in each; Adopt calibration set sample to be optimized model, optimize the content comprises signal selection, number of principal components, preprocess method.During optimization, using the result of leave one cross validation as criterion, from calibration set sample, reject a sample at every turn, and adopt other samples to carry out modeling, with institute's established model, to rejecting sample, predict, judge whether it is Donga donkey-hide gelatin, calibration set all samples all can be once predicted like this, usings total False Rate as criterion, preferably modeling parameters.In the present embodiment, finally determine, select 17 signals on sensor to carry out modeling, number of principal components is 6.The fiducial interval of setting F check is 95% (being 1-α, α=0.05).
According to the step of above-mentioned collected specimens data, gather the sample data of donkey-hide gelatin sample to be detected, this sample data is carried out to pre-service by transformation for mula above, by principal component analysis (PCA) discrimination model described in the sample data substitution of donkey-hide gelatin sample to be detected, the number of principal components that obtains donkey-hide gelatin sample to be detected according to and the distance at the major component center of the principal component analysis (PCA) discrimination model of described training collection, and according to this apart from the F calculated value F that calculates the homogeneity test of variance of donkey-hide gelatin sample to be detected
calculate, according to the fiducial interval of the homogeneity test of variance classification of setting, by F
calculatecritical value F with the level of significance α place setting
criticalcompare, level of significance α=0.05 in the present embodiment, if F
calculated value﹤ F
critical, there is not significant difference in donkey-hide gelatin sample to be detected and Donga donkey-hide gelatin sample, and regarding as donkey-hide gelatin sample to be detected is Donga donkey-hide gelatin, if F
calculated value﹥ F
critical, there is significant difference in donkey-hide gelatin sample to be detected and Donga donkey-hide gelatin sample, and regarding as test sample donkey-hide gelatin to be checked is not originally Donga donkey-hide gelatin.As shown in Figure 3, be the sample data of an adulterant donkey-hide gelatin; Fig. 4 is the sample data of other brand donkey-hide gelatin.
One of ordinary skill in the art will appreciate that: accompanying drawing is the schematic diagram of an embodiment, the module in accompanying drawing or flow process might not be that enforcement the present invention is necessary.
One of ordinary skill in the art will appreciate that: the module in the device in embodiment can be described and be distributed in the device of embodiment according to embodiment, also can carry out respective change and be arranged in the one or more devices that are different from the present embodiment.The module of above-described embodiment can be merged into a module, also can further split into a plurality of submodules.
Finally it should be noted that: above embodiment only, in order to technical scheme of the present invention to be described, is not intended to limit; Although the present invention is had been described in detail with reference to previous embodiment, those of ordinary skill in the art is to be understood that: its technical scheme that still can record previous embodiment is modified, or part technical characterictic is wherein equal to replacement; And these modifications or replacement do not make the essence of appropriate technical solution depart from the spirit and scope of embodiment of the present invention technical scheme.
Claims (8)
1. utilize Electronic Nose Technology to differentiate a method for donkey-hide gelatin, it is characterized in that, comprise the following steps:
A) the donkey-hide gelatin product of choosing particular vendors is as sample;
B) each sample in described sample is detected, testing process is:
B1) the broken end of sample after sample is pulverized and sieved takes 0.5-2.0g and is placed in the sealing specimen bottle that volume is 5-20ml, stirs 1000s-3000s, the gas in described specimen bottle is got to entry needle for 1-5ml and inject Electronic Nose air chamber; In described Electronic Nose air chamber, be provided with 3 chambers, described 3 chambers are provided with totally 18 sensor arraies that sensor forms;
B2) described sensor array gathers the sample data in described specimen bottle; Wherein, the sample data of each sample gathers 3 times, averages; The sample data gathering is the characteristic response spectrum of sample smell;
C) to all samples data in this sample, be divided into calibration set data and checking collection data, adopt described calibration set data to set up discrimination model, and by described checking collection data, set up discrimination model is verified;
The method that wherein adopts described calibration set data to set up discrimination model is:
C1) data of single sample are carried out to pre-service, characteristic information extraction also carries out following conversion:
Wherein, SNV
iit is the standard normal variable of i sensor response in the Electronic Nose signal of single sample; x
ibe the response of i sensor in this single sample;
the mean value of all the sensors response in the Electronic Nose signal of this single sample; P is the number of probes in Electronic Nose air chamber; I is natural number, and its span is from 1 to p;
C2) obtain all samples data after pretreatment in calibration set, adopt SIMCA method to principal component analysis (PCA) discrimination model of this Sample Establishing, first using the sample in described calibration set as a training set, the sample data matrix of described training set is carried out respectively to principal component analysis (PCA), set up the principal component analysis (PCA) discrimination model of described training set and with leaving-one method, described principal component analysis (PCA) discrimination model be optimized; Wherein said sample data matrix is comprised of the peak value of the response of p sensor;
D) according to the method for step b, gather the sample data of donkey-hide gelatin sample to be detected, and according to the method for step c1, the sample data of donkey-hide gelatin sample to be detected is carried out to pre-service, by principal component analysis (PCA) discrimination model described in the sample data substitution of donkey-hide gelatin sample to be detected, the number of principal components that obtains donkey-hide gelatin sample to be detected according to and the distance at the major component center of the principal component analysis (PCA) discrimination model of described training collection, and according to this apart from the F calculated value F that calculates the homogeneity test of variance of donkey-hide gelatin sample to be detected
calculate, according to the fiducial interval of the homogeneity test of variance classification of setting, by F
calculatecritical value F with the level of significance α place setting
criticalcompare, judge whether the precision of donkey-hide gelatin sample to be detected and described principal component analysis (PCA) discrimination model has significant difference, if F
calculate﹤ F
critical, there is not significant difference in the donkey-hide gelatin sample of donkey-hide gelatin sample to be detected and this particular vendors, regards as the donkey-hide gelatin that donkey-hide gelatin sample to be detected is this particular vendors, if F
meter calculate﹥ F
critical, there is significant difference in the donkey-hide gelatin sample of donkey-hide gelatin sample to be detected and this particular vendors, regards as the donkey-hide gelatin that donkey-hide gelatin sample to be detected is not this particular vendors.
2. the method for utilizing Electronic Nose Technology to differentiate donkey-hide gelatin according to claim 1, is characterized in that, this sample that step is chosen in a) at least has 20 samples.
3. the method for utilizing Electronic Nose Technology to differentiate donkey-hide gelatin according to claim 1, it is characterized in that, described sensor array comprises strong oxidability gas sensor, toxic gas sensor, organic compound sensor, inflammable gas sensor and aromatics sensor.
4. the method for utilizing Electronic Nose Technology to differentiate donkey-hide gelatin according to claim 1, is characterized in that, the temperature of described entry needle is 80 ℃-150 ℃, and injection speed is 1-5ml/s.
5. the method for utilizing Electronic Nose Technology to differentiate donkey-hide gelatin according to claim 1, is characterized in that, the acquisition time that described sensor array gathers the sample data in described specimen bottle is 60-600s.
6. the method for utilizing Electronic Nose Technology to differentiate donkey-hide gelatin according to claim 1, is characterized in that, the speed that sample stirs in described specimen bottle is 300-900rpm.
7. the method for utilizing Electronic Nose Technology to differentiate donkey-hide gelatin according to claim 1, is characterized in that, the temperature that sample produces gas in described specimen bottle is 50 ℃-150 ℃.
8. the method for utilizing Electronic Nose Technology to differentiate donkey-hide gelatin according to claim 1, is characterized in that, the level of significance α of setting is 0.05.
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| CN105044161A (en) * | 2015-07-03 | 2015-11-11 | 宁波大学 | Method for discriminating furacilin and furazolidone in Tegillarca granosa by using electron nose |
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