CN108103138A - The exceeded quick discrimination method of fresh sheep breast total plate count based on dielectric and magnetic technology - Google Patents
The exceeded quick discrimination method of fresh sheep breast total plate count based on dielectric and magnetic technology Download PDFInfo
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- CN108103138A CN108103138A CN201810114089.2A CN201810114089A CN108103138A CN 108103138 A CN108103138 A CN 108103138A CN 201810114089 A CN201810114089 A CN 201810114089A CN 108103138 A CN108103138 A CN 108103138A
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- G01N27/22—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating capacitance
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Abstract
The invention discloses a kind of exceeded quick discrimination methods of fresh sheep breast total plate count based on dielectric and magnetic technology, comprise the following steps：Using dielectric property measuring instrument in whole frequency range, a collection of not exceeded dielectric and magnetic with exceeded fresh sheep milk sample sheet of total plate count is obtained.Original dielectric frequency spectrum is pre-processed, and calibration set and forecast set are obtained using the sample division methods of qualitative analysis.Dielectric and magnetic data are compressed using principal component analysis and successive projection algorithm.The model for differentiating that fresh sheep breast total plate count is exceeded is established, and the differentiation accuracy rate of each model is verified.Wherein the supporting vector machine model based on principal component analysis is optimal models, which is 100% to the differentiation accuracy rate of calibration set and forecast set.Differentiate whether fresh sheep breast total plate count exceeded the present invention is based on dielectric and magnetic technology, have many advantages, such as it is quick, efficient, convenient, accurate, complex sample preparation is not required.
Description
Technical field
The present invention relates to total plate count detection technique field, more particularly to a kind of fresh sheep based on dielectric and magnetic technology
The newborn exceeded quick discrimination method of total plate count.
Background technology
Food may all be polluted in the links such as production, processing, storage, transport, sale by microorganism.Once food
Product are contaminated, and amount reproduction is caused food apoilage or causes Diet_induced obesity and food poisoning by microorganism.Sheep breast is
The deep food favored by consumers in general.Contain abundant nutritional ingredient, such as absorbable protein, fat in sheep breast
Fat, carbohydrate and mineral trace element etc..Due to being rich in a variety of nutriments, sheep breast is more prone to compared to other food by micro-
Biological pollution.Total plate count is excessively high in breast, can not only cause breast spoiled, but also likely result in using breast as the other of primary raw material
The bacterium colony of dairy products is exceeded.《Fresh milk acquisition criteria》（GB19301-2010）The total plate count upper limit is set to 2,000,000 CFU/mL.
The method of traditional detection total plate count is Standard Plate Count method, although this method is accurate, needs to consume the plenty of time.Cause
This this method is not suitable for being applied to quick online detection.Some researchers are proposed including formula cytometry, bioluminescence ATP
The rapid detection methods such as method, electrical impedance method, volt-ampere analysis.But in these methods, some are expensive, some are complicated for operation,
Some methods need the long period to carry out bacterium colony culture.Therefore propose that quick, easily fresh sheep breast total plate count is exceeded quick
Method of discrimination is most important to the production and consumption of fresh sheep breast and its dairy products.
Dielectric property has become widely applied since it has many advantages, such as quick and need not be complicated sample preparation
Food analysis method.The dielectric property of material belongs to as acoustics, optics, magnetics etc. in substance with other physical characteristics
Characteristic.It is many research report points out, the dielectric property of food is influenced by its ingredient, for example, moisture, pol, fat, can
Dissolubility solid content etc..In recent years, dielectric property detection technique has also been employed that moisture, fat, the protein of detection fresh milk contain
In amount.Up to the present, there is not yet predicting the whether exceeded research of the total plate count of large sample fresh milk based on dielectric and magnetic.For
This, it is necessary to a kind of exceeded quick discrimination method of fresh sheep breast total plate count based on dielectric and magnetic technology is developed, is disappeared with ensureing
The rights and interests of the person of expense, while promote the sound development of sheep breast industry, safeguard China's Food safety and health.
The content of the invention
In view of above-mentioned prior art current situation, the object of the present invention is to provide a kind of based on the fresh of dielectric and magnetic technology
The exceeded quick discrimination method of sheep breast total plate count.Using dielectric property measuring instrument, it is not exceeded and exceeded to gather a collection of total plate count
The dielectric and magnetic of sheep milk sample sheet.Based on dielectric and magnetic data, the fresh exceeded discrimination model of sheep breast total plate count is established.The present invention's
Method can be used in the exceeded quick discrimination of Fresh Milk total plate count.
The exceeded quick discrimination method of fresh sheep breast total plate count based on dielectric and magnetic technology, comprises the following steps：
Step 1 chooses the not exceeded and exceeded fresh sheep breast of total plate count and is used as sample；According to national standard method detection sample
Total plate count, and differentiate whether its total plate count is exceeded according to national standard.
Step 2 preheats dielectric property measuring instrument, and uses normal process calibration instrument；Acquisition software is set, including frequency
Rate scope, scan mode, frequency points；Fresh sheep milk sample product are uniformly mixed using blender, under 25 DEG C of constant temperature, full rate
In the range of, measure the dielectric and magnetic of sample；The dielectric and magnetic includes dielectric constant frequency spectrum and dielectric dissipation factor frequency spectrum.
Step 3 pre-processes dielectric and magnetic；Due to the presence of noise, the head and tail parts of removal dielectric constant frequency spectrum；Then
Smoothly become scaling method with standard normal using Savitzky-Golay and original dielectric frequency spectrum is pre-processed.
Step 4, using kennard-Stone sample division methods, according to 2:1 or 3:1 or 4:1 ratio, by fresh sheep
Milk sample is originally divided into calibration set and forecast set；Ensure ratio phase of the not exceeded and exceeded sample of total plate count in calibration set and forecast set
Together.
Step 5, using Principal Component Analysis and successive projection algorithm, to the dielectric and magnetic of the fresh sheep milk sample sheet of calibration set
Carry out data compression；Based under different number of principal components, the forecast set of partial least squares discriminant analysis model differentiates accuracy rate, chooses
Optimal number of principal components；According to the average risk G values under different characteristic variable number, suitable feature under successive projection algorithm is determined
Variable number；Same compression processing is carried out to forecast set dielectric and magnetic.
Step 6 using compressed calibration set dielectric and magnetic, establishes the fresh exceeded discrimination model of sheep breast total plate count；Make
Model is verified with compressed forecast set dielectric and magnetic；Differentiation accuracy rate based on each model calibration set and forecast set,
Comparison determines that best model is the supporting vector machine model based on principal component analysis.
Step 7 for fresh sheep milk sample sheet to be measured, obtains dielectric and magnetic according to step 2 and step 3, uses principal component
Analytic approach carries out data compression to dielectric and magnetic, then using compressed data as the support vector machines based on principal component analysis
The input of model draws differentiation result.
This method applies also for the exceeded quick discrimination of Fresh Milk total plate count.
Wherein, in step 2, fresh sheep milk sample product are uniformly mixed using blender first, then in 25 DEG C of constant temperature
Under, in whole frequency range, measure the dielectric and magnetic of fresh sheep breast.
The whole frequency range refers to the entire detection frequency range of the dielectric property measuring instrument or detection frequency
In the range of a certain section.
The invention has the advantages that：The present invention obtains Jie of fresh sheep breast by detecting the dielectric property of fresh sheep breast
Electric frequency spectrum.Using different data prediction and compression method, the principal component and characteristic variable of dielectric and magnetic are obtained, establishes identification
The exceeded discrimination model of sheep breast total plate count.The differentiation accuracy rate of calibration set and forecast set is drawn most preferably by comparing each model
Model provides a kind of fast method for the exceeded differentiation of sheep breast total plate count.
Description of the drawings
Fig. 1：Forecast set based on partial least squares discriminant analysis model under different number of principal components differentiates accuracy rate；
Fig. 2：Average risk G values in successive projection algorithm preferred feature multivariable process under different characteristic variable number.
Specific embodiment
The method of the present invention is exceeded to different fresh sheep breast total plate counts to differentiate there is good versatility.Due to fresh sheep breast it is more
Sample, only using the produced fresh sheep breast of Sa energy Rushan sheep as embodiment, other fresh sheep breast total plate counts are exceeded to be sentenced the present invention
The method that not can refer to the embodiment carries out.With specific reference to surveyed dairy products, corresponding discrimination model is established, it is possible to for the life
The exceeded quick discrimination of fresh sheep breast total plate count.
The invention will be further described with reference to the accompanying drawings and examples.
Method according to the embodiment of the present invention comprises the following steps：
Step 1 chooses the fresh sheep milk sample sheet of a collection of different breeding field and different lactation, passes through the tablet meter of national regulations
Number method detection total plate count, and according to fresh milk total plate count no more than 2,000,000 CFU/mL of national regulations, differentiate its bacterium colony
Whether sum is exceeded；Select not exceeded and exceeded fresh sheep milk sample product similar in quantity；Fresh sheep breast in the present embodiment is adopted
The Sa energy Rushan sheep cultivation casual households different from Xianyang, Shanxi province city Yangling District 5, obtain the not exceeded sample of 77 total plate counts and
73 exceeded samples of total plate count.
Step 2 preheats dielectric property measuring instrument, and calibrates dielectric property measuring instrument using normal process；Set acquisition soft
Part, including frequency range, scan mode, frequency points；In the present embodiment, dielectric property measuring instrument is by Agilent company of the U.S.
E5071C vector network analyzers and 85070E coaxial probes are formed；Setting frequency range is 20-4500 MHz, and scan mode is
Logarithm, scan frequency points are 201；Fresh sheep milk sample product are uniformly mixed using blender, at 25 DEG C, whole frequency range
That is in 20-4500MHz, 201 dielectric constants of the inferior interval acquiring of logarithmic coordinates and 201 dielectric dissipation factors；By 201 Jie
Electric constant is labeled as the 1-201 point of dielectric and magnetic, and 201 dielectric dissipation factors are labeled as to the 202- of dielectric and magnetic
Thus 402 points form the dielectric and magnetic of sample.
Step 3 pre-processes dielectric and magnetic.Remove each 25 points of dielectric and magnetic medium dielectric constant microwave medium frequency spectrum head and the tail, i.e. dielectric frequency
1-15 and 176-201 data points in spectrum, remaining 352 points form new dielectric and magnetic；It is put down first with Savitzky-Golay
Then high-frequency noise in sliding removal dielectric and magnetic becomes scaling method using standard normal and further pre- place is carried out to dielectric and magnetic
Reason.
Step 4, using the kennard-Stone sample division methods suitable for qualitative analysis, according to 3:1 ratio, will
Sheep milk sample is originally divided into calibration set and forecast set.It is divided for not exceeded and exceeded sample standard deviation using kennard-Stone samples
Method is according to 3:1 ratio cut partition is calibration set and forecast set；Then merge respectively the calibration set of not exceeded and exceeded sample with
The forecast set of not exceeded and exceeded sample, last calibration set have 113, sample, wherein not exceeded 58, sample, exceeded sample 55
It is a；Forecast set has 37, sample, wherein not exceeded 19, sample, exceeded 18, sample.
Step 5, using Principal Component Analysis and successive projection algorithm, to the dielectric and magnetic of the fresh sheep milk sample sheet of calibration set
It is compressed.
The partial least squares discriminant analysis model under 1-15 principal component is established, the differentiation for calculating each model prediction collection is accurate
Rate, as shown in Figure 1.It chooses differentiation accuracy rate highest and the smaller number of principal components of number of principal components is as optimal number of principal components；This
Method has chosen 13 principal components as mode input, and accumulation contribution rate is 99.97%.
When extracting dielectric and magnetic feature using successive projection algorithm, feature is determined according to the average risk G values of calibration set
Variable number；With the increase of characteristic variable number, the variation of G values is as shown in Fig. 2, the point for selecting G values minimum is best features variable
Number；17 variables has been selected to include 2 dielectric constants respectively as characteristic variable in the present embodiment（Frequency is respectively
116.15 with 2125.45 MHz）With 15 dielectric dissipation factors（Frequency is 22.16,22.88,25.03,25.75,26.47,
27.91st, 30.06,32.22,35.61,40.55,46.73,86.69,300.00,3464.98 and 4029.54MHz）.
Step 6 using compressed calibration set dielectric and magnetic, establishes the fresh exceeded discrimination model of sheep breast total plate count；
Using 13 principal components and 17 characteristic variables in the present embodiment, extreme learning machine and supporting vector machine model are established respectively；Make
Model is verified respectively with compressed calibration set and forecast set dielectric and magnetic, based on accuracy rate is differentiated, comparison is determined
Best model；In four models established, the extreme learning machine model based on principal component analysis is to calibration set and forecast set
Differentiate that accuracy rate is respectively 93.8% and 91.9%, based on the supporting vector machine model of principal component analysis to calibration set and forecast set
Differentiate that accuracy rate is 100%, the extreme learning machine model based on successive projection algorithm is accurate to the differentiation of calibration set and forecast set
Rate is respectively 99.1% and 100%, and the supporting vector machine model based on successive projection algorithm is accurate to the differentiation of calibration set and forecast set
True rate is respectively 93.8% and 97.3%, therefore best model is the supporting vector machine model based on principal component analysis.
Step 7 for fresh sheep milk sample sheet to be measured, obtains dielectric and magnetic first, in accordance with step 2 and step 3, uses master
Componential analysis is compressed dielectric and magnetic；Then using compressed data as the support vector machines based on principal component analysis
The input of model draws differentiation result.
As can be seen from the above embodiments, the present invention differentiates whether sheep breast total plate count is exceeded using dielectric and magnetic technology,
It can not only realize quick discrimination, and effect is fine.
The above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, without departing from the technical principles of the invention, several improvement and modification, these improvements and modifications can also be made
Also it should be regarded as protection scope of the present invention.
Claims (4)
1. the exceeded quick discrimination method of fresh sheep breast total plate count based on dielectric and magnetic technology, which is characterized in that including following
Step：
Step 1 chooses the not exceeded and exceeded fresh sheep breast of total plate count and is used as sample；According to national standard method detection sample
Total plate count, and differentiate whether its total plate count is exceeded according to national standard；
Step 2 preheats dielectric property measuring instrument, and uses normal process calibration instrument；Acquisition software is set, including frequency model
It encloses, scan mode, frequency points；Fresh sheep milk sample product are uniformly mixed using blender, under 25 DEG C of constant temperature, whole frequency range
It is interior, measure the dielectric and magnetic of sample；The dielectric and magnetic includes dielectric constant frequency spectrum and dielectric dissipation factor frequency spectrum；
Step 3 pre-processes dielectric and magnetic；Due to the presence of noise, the head and tail parts of removal dielectric constant frequency spectrum；Then utilize
Savitzky-Golay is smooth and standard normal becomes scaling method and original dielectric frequency spectrum is pre-processed；
Step 4, using kennard-Stone sample division methods, according to 2:1 or 3:1 or 4:1 ratio, by fresh sheep milk sample
Originally it is divided into calibration set and forecast set；Ensure that total plate count is not exceeded identical with the ratio of forecast set in calibration set with exceeded sample；
Step 5 using Principal Component Analysis and successive projection algorithm, carries out the dielectric and magnetic of the fresh sheep milk sample sheet of calibration set
Data compression；Based under different number of principal components, the forecast set of partial least squares discriminant analysis model differentiates accuracy rate, chooses optimal
Number of principal components；According to the average risk G values under different characteristic variable number, suitable characteristic variable under successive projection algorithm is determined
Number；Same compression processing is carried out to forecast set dielectric and magnetic；
Step 6 using compressed calibration set dielectric and magnetic, establishes the fresh exceeded discrimination model of sheep breast total plate count；Use pressure
Forecast set dielectric and magnetic after contracting verifies model；Differentiation accuracy rate based on each model calibration set and forecast set, comparison
It is the supporting vector machine model based on principal component analysis to determine best model；
Step 7 for fresh sheep milk sample sheet to be measured, obtains dielectric and magnetic according to step 2 and step 3, uses principal component analysis
Method carries out data compression to dielectric and magnetic, then using compressed data as the supporting vector machine model based on principal component analysis
Input, draw differentiation result.
2. the fresh sheep breast total plate count exceeded quick discrimination method according to claim 1 based on dielectric and magnetic technology,
It is characterized in that, this method applies also for the exceeded quick discrimination of Fresh Milk total plate count.
3. the fresh sheep breast total plate count exceeded quick discrimination method according to claim 1 based on dielectric and magnetic technology,
It is characterized in that, in step 2, it is uniformly mixed fresh sheep milk sample product using blender first, then under 25 DEG C of constant temperature,
In whole frequency range, the dielectric and magnetic of fresh sheep breast is measured.
4. the fresh exceeded quick discrimination side of sheep breast total plate count based on dielectric and magnetic technology according to claim 1 or 3
Method, which is characterized in that the whole frequency range refers to entire detection frequency range or the inspection of the dielectric property measuring instrument
A certain section in the range of measured frequency.
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| CN114087940A (en) * | 2021-11-18 | 2022-02-25 | 得力集团有限公司 | Use method of multifunctional vernier caliper |
| CN114087940B (en) * | 2021-11-18 | 2024-05-31 | 得力集团有限公司 | Use method of multifunctional vernier caliper |
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Application publication date: 20180601 |