CN1804582A - Method for identifying reductive milk in fresh milk and commodity milk by using near infrared spectrum - Google Patents
Method for identifying reductive milk in fresh milk and commodity milk by using near infrared spectrum Download PDFInfo
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Abstract
The invention provides a method for using near infrared spectra to identify the reduction milk-like liquid of fresh milk and product milk, which comprises the following steps: first doing front process to the sample with known reduction milk-like liquid content, collecting the sample's near infrared spectra, establishing the qualitative or quantitative identifying model, collecting the near infrared spectra of the unknown sample to do data process and doing qualitative or quantitative identifying.
Description
Technical field
The present invention relates to the dairy products detection range, relate to a kind of method of utilizing near infrared spectrum to differentiate the recombined milk in fresh breast and commodity Ruzhong particularly.
Background technology
Fresh breast is as the base stock of cow's milk manufacturer, and its quality control is vital in production management.Generally, recombined milk is exactly to add water with milk powder to blend the milk that reduction forms, and its nutritive value can not show a candle to fresh breast.
Now, a lot of businessmans serve as fresh breast with cheap recombined milk and sell on market in order to obtain commercial profit.Also have some producers to utilize not have strict, unified standard to come the leak of standard market, add cheap recombined milk in low-quality fresh Ruzhong, every conventional index of cow's milk is up to state standards, sell with the fresh breast competition of high-quality, influenced the normal operation in market, and the fresh newborn nutritive value that adds recombined milk greatly reduces, and directly damaged consumer's interests.
Selling with making fresh milk after the recombined milk processing, is a kind of fraud to the consumer.For this reason, the General Office of the State Council has issued " about strengthening the notice of liquid milk production and operation " on September 17th, 2005, requires industry to strengthen self-discipline, safeguards consumer's interests conscientiously.But because a variety of causes, some Dairy Production producers have lucky psychology in arms and still do not give tangible mark on its recombined milk product.
At present, detection department of country for the detection of recombined milk mainly be according in the heat treatment process since the variation of temperature, the different caused cow's milk internal component of time differentiate, the variation that utilizes the original composition of cow's milk on the one hand is as the identification indicant, for example newborn hydrogen peroxidase, lactalbumin; Utilize the novel substance that generates in the heat treatment process as the identification indicant on the other hand, for example chaff propylhomoserin, hydroxymethylfurfural, for example " standard of perfection of pasteurization milk and ultra high temperature short time sterilization Ruzhong reconstituted milk " of the nearest promulgation of the Ministry of Agriculture judges according to the content of newborn chaff propylhomoserin in the liquid state and two kinds of materials of lactulose whether pasteurization milk and ultra high temperature short time sterilization Ruzhong contain recombined milk exactly.The result is more accurate for these detection methods, but complicated operation waste time and energy, and required instrument costliness, reagent is various.For example doing the detection of discerning indicant with the chaff propylhomoserin needs two days ability to handle a sample, and the method for utilizing lactulose to do the identification indicant also needs one day ability to handle a sample.
Obviously, these prior aries can not satisfy at the scene fast, accurately differentiate the needs of recombined milk.Seek a kind of reliable, easy again fast way judge the formation and the quality of dairy products, the law enforcement and the protection consumer's interests of technical supervision department are all had important meaning.
Near infrared technology as a kind of fast, accurately, do not have the green test technology of destroying, guaranteed the integrality and the edibility of sample.The present invention adopts near-infrared spectrum technique to detect recombined milk, for rapid evaluation dairy products source provides an otherwise effective technique approach, important practical sense and using value is arranged.
Summary of the invention
(1) technical matters that will solve
The purpose of this invention is to provide a kind of easy and simple to handlely, with low cost, convenient and swift, the result differentiates the method for the recombined milk in fresh breast and commodity Ruzhong accurately.
(2) technical scheme
The method of utilizing near infrared spectrum to differentiate the recombined milk in fresh breast and commodity Ruzhong of the present invention, it may further comprise the steps:
(1) pre-treatment of sample;
(2) near infrared spectra collection of sample;
(3) set up qualitative or the quantitative identification model;
(4) unknown sample is gathered near infrared spectrum, carry out data processing, utilize the model of setting up in the step (3) to handle, make qualitative or quantitative identification.
Method of the present invention, sample pre-treatments is: fresh breast or commodity breast is mixed with recombined milk, be mixed with recombined milk concentration and be respectively 0,10%, 20%, 33%, 50%, 66%, 80%, 100% sample.
Method of the present invention, the near infrared spectra collection of sample is with sample constant temperature to 40 ± 0.1 ℃, (U.S. Thermo Nicolet company produces to use the Fourier transform near infrared spectrometer then, model ANTARIS), the spectrum of associative multiplication bulb separation annex collected specimens, detecting wavelength coverage is 800～2500nm, is spaced apart 2nm.Earlier pour sample into diameter 2cm during each the collection, in the cylindrical sample cup of high 5cm, then sample cup being placed hot spot is on the integrating sphere of 0.9cm.For preventing that light from directly seeing through sample, should guarantee liquid level greater than 4cm, to eliminate the spectrum differences that thickness of sample causes.Each sample collecting 3 times scans 64 times at every turn and is averaged, by the computer recording absorbance (log1/R) that links to each other.
Method of the present invention, wherein, the foundation of qualitative discrimination model may further comprise the steps:
(1) data processing: the characteristic wave bands of one or more among the full spectrum of selection 800～2500nm or 900～1000nm, 1000～1200nm, the 1100～2500nm is set up model, utilize methods such as polynary scatter correction processing, standard normal conversion, first derivation, second order differentiate and multiple spot are level and smooth successively spectroscopic data to be optimized processing, and the graph of a relation rejecting abnormalities sample of chemical score tization residual error and mahalanobis distance value per sample, these data processing all utilize TQ Analyst V6.2 process software (U.S. Thermo Nicolet company) to carry out;
(2) set up model: the discriminatory analysis function of utilizing TQ Analyst V6.2 process software (U.S. Thermo Nicolet company) is carried out principal component analysis (PCA) respectively to the spectroscopic data matrix of variable concentrations sample, sets up the principal component analysis (PCA) mathematical model.
Method of the present invention, when unknown sample is made qualitative identification, utilize TQ Analyst V6.2 process software that the optimization spectroscopic data of unknown sample is carried out the major component decomposition earlier, in the major component space of each class, carry out the mahalanobis distance computing, obtain the distance of each class sample, utilize the qualitative discrimination model of building to handle, draw identification result.
The present invention finds that under study for action fresh breast and recombined milk have following difference: fresh breast does not pass through any pre-service, and it has characteristic absorption peak at 1880～1888nm; And recombined milk is handled through homogeneous, and it has characteristic absorption peak at 1890～1898nm.Utilize the difference of the characteristic absorption peak of recombined milk and fresh breast, directly the second derivative figure according to spectrum makes qualitative identification.
Method of the present invention, wherein, the foundation of quantitative identification model may further comprise the steps:
(1) data processing: the characteristic wave bands of one or more among the full spectrum of selection 800～2500nm or 900～1000nm, 1000～1200nm, the 1100～2500nm is set up model, utilize methods such as polynary scatter correction processing, standard normal conversion, first derivation, second order differentiate and multiple spot are level and smooth successively spectroscopic data to be optimized processing, and the graph of a relation rejecting abnormalities sample of chemical score tization residual error and mahalanobis distance value per sample, these data processing all utilize TQ Analyst V6.2 process software (U.S. Thermo Nicolet company) to carry out;
(2) set up model: utilize partial least square method, set up the relational model between sample concentration and the near infrared spectrum.Utilize related coefficient (R), model standard deviation (RMSECV) to come the quality of judgment models then, up to the model that obtains R maximum, RMSECV minimum.
It is 0.971 that the present invention obtains related coefficient, and the model standard deviation is 7.76% quantitative identification model.
Method of the present invention when unknown sample is made quantitative identification, is brought the optimization spectroscopic data of unknown sample the quantitative identification model of foundation into, utilizes TQ Analyst V6.2 process software to calculate the amount of recombined milk in the unknown sample.
Method of the present invention can be used for differentiating the recombined milk in commodity Ruzhong.
On meaning of the present invention, fresh breast is meant the normal breast of forcing down from healthy dairy stock, without pasteurization or be lower than the thermal treatment of pasteurization, clean breast is handled and other sterilization processing.
Recombined milk is meant the raw milk that blends into condensed milk and/or whole-fat milk powder and water.
The commodity breast is meant through pasteurization or ultra high temperature short time sterilization and handles, for the dairy products of selling.
Mahalanobis distance is meant the distance between 2 in the defined space of two or more correlated variabless.
The tization residual error is meant the value that residual error obtains divided by its standard error.
(3) beneficial effect
Method of the present invention is compared with classic method, has the following advantages:
1. accuracy height, good reproducibility: for the qualitative detection of recombined milk, when the recombined milk incorporation was in 10%, the correct decision rate reached 96.7%; When the recombined milk incorporation reaches 20% when above, the correct decision rate reaches 100% and since in the market the fresh breast of selling and commodity Ruzhong mix recombined milk ratio all far above 20%, so this method can well realize the discriminating to recombined milk;
2. this method is in qualitative identification, and the incorporation of detection recombined milk that can also be quantitative is differentiated quite ideal of result, and the related coefficient of model prediction reaches 0.971, and standard deviation is 7.76%;
3. detection speed is fast: just can determine whether mixed recombined milk in the sample within one minute;
4. environmental protection, with low cost: this method without any need for chemical reagent, had both been avoided the pollution of chemical reagent to environment after modelling, had saved the expense of buying reagent again, effectively reduced enterprise cost;
5. easy and simple to handle: after model was built up, only needing operating personnel are simply trained can be on duty.
Method of the present invention can well reach the requirement of differentiating recombined milk, thereby protects consumer's rights and interests to greatest extent, and the while also provides strong assurance for the law enforcement of technical supervision department.
Description of drawings
Fig. 1 contains the identification result of the fresh breast of 20% recombined milk, and among the figure: square is represented fresh newborn sample, and triangle is represented the recombined milk sample;
The identification result of Fig. 2 commodity Ruzhong recombined milk, among the figure: square is represented commodity breast sample, and triangle is represented the recombined milk sample;
The feature of fresh breast of Fig. 3 and recombined milk is differentiated wavelength;
Related coefficient figure between Fig. 4 recombined milk predicted value and chemical score is among the figure: the circle representative sample.
Embodiment
Following examples are used to illustrate the present invention, but are not used for limiting the scope of the invention.
The qualitative identification of embodiment 1 fresh Ruzhong recombined milk
1. the pre-treatment of sample:
(1) obtaining of fresh newborn sample: take from three holstein cows in China Agricultural University Sino-U.S. dairy industry research centre, sampling at noon every day totally 5 days, is put into 4 ℃ of portable refrigerator refrigerations and is transported back after the collection;
(2) obtaining of recombined milk sample: buy the full-cream fresh milk powder of Erie from the market, every 25g milk powder adds 180mL warm water and reconstitutes, shake up be cooled to after the room temperature standby.Recording its fat content by classical chemical method is 3.68%, and protein content is 3.33%, and density is 1.026, approaching with the average data of the used fresh breast of experiment, can eliminate the differentiation distortion as a result that causes because of content difference.
(3) preparation of different gradient recombined milks: according to recombined milk concentration is 0,10%, 20%, 33%, 50%, 66%, 80%, 100% gradient, carries out the preparation of fresh breast and recombined milk.Obtain altogether to comprise 8 kinds of the different gradient laboratory samples of fresh breast, 15 every kind, 120 of total number of samples.
2. near infrared spectra collection
With sample constant temperature to 40 ± 0.1 ℃, use Fourier transform near infrared spectrometer (U.S. ThermoNicolet company produces, model ANTARIS) then, the diffuse reflection spectrum of associative multiplication bulb separation annex collected specimens, detecting wavelength coverage is 800～2500nm, is spaced apart 2nm.Earlier pour sample into diameter 2cm during each the collection, in the cylindrical sample cup of high 5cm, then sample cup being placed hot spot is on the integrating sphere of 0.9cm.Each sample collecting three times scans 64 times at every turn and averages, by the computer recording absorbance that links to each other.
3. set up qualitative discrimination model:
(1) data processing: select the full spectrum of 800～2500nm to set up model, utilize methods such as polynary scatter correction processing, standard normal conversion, first derivation, second order differentiate and multiple spot are level and smooth successively spectroscopic data to be optimized processing, and the graph of a relation rejecting abnormalities sample of chemical score tization residual error and mahalanobis distance value per sample, these data processing all utilize TQ Analyst V6.2 process software (U.S. ThermoNicolet company) to carry out;
(2) set up model: the discriminatory analysis function of utilizing TQ Analyst V6.2 process software (U.S. Thermo Nicolet company) is carried out principal component analysis (PCA) respectively to the spectroscopic data matrix of variable concentrations sample, sets up the principal component analysis (PCA) mathematical model.
4. make qualitative identification:
Adopt the described method of step 2 that unknown sample is gathered near infrared spectrum, adopt (1) described method of step 3 to carry out data processing, utilize TQ Analyst V6.2 process software that the optimization spectroscopic data of unknown sample is carried out the major component decomposition then, in the major component space of each class, carry out the mahalanobis distance computing, obtain the distance of each class sample, utilize in the step 3 qualitative discrimination model of building to handle, draw identification result.
Identification result is: for the sample that contains 10% recombined milk, have 1 fresh newborn sample to be mistaken for recombined milk, do not have the recombined milk sample to be mistaken for fresh breast, accuracy reaches 96.7%; When recombined milk concentration reaches 20% when above, this method can be carried out 100% correct discriminating.In the differentiation process,, do not influence discriminating to the recombined milk sample though the erroneous judgement of some is arranged between different gradient recombined milk.
The qualitative identification of embodiment 2 commodity Ruzhong recombined milks
Difference from Example 1 is: the commodity breast in the sample pre-treatments is the liquid fresh milk of commercially available different manufacturers; What choose when setting up qualitative discrimination model is the characteristic wave bands of 900～1000nm, 1000～1200nm and 1100～2500nm.
Identification result is: 2 erroneous judgements are arranged in 80 samples, and accuracy reaches 97.5%.
The qualitative identification of embodiment 3 fresh Ruzhong recombined milks
Difference from Example 1 is: at 1884nm characteristic absorption peak is arranged according to fresh breast, recombined milk has the difference of characteristic absorption peak at 1895nm, the spectroscopic data of gathering is after TQ Analyst V6.2 process software (U.S. Thermo Nicolet company) is handled, and directly the second derivative figure according to spectrum makes qualitative identification.
Identification result is: accuracy is up to 100%.
The foundation of the quantitative identification model of embodiment 4 fresh Ruzhong recombined milks
1. the pre-treatment of sample:
(1) obtaining of fresh newborn sample: take from three holstein cows in China Agricultural University Sino-U.S. dairy industry research centre, sampling at noon every day totally 5 days, is put into 4 ℃ of portable refrigerator refrigerations and is transported back after the collection;
(2) obtaining of recombined milk sample: buy the full-cream fresh milk powder of Erie from the market, every 25g milk powder adds 180mL warm water and reconstitutes, shake up be cooled to after the room temperature standby.Recording its fat content by classical chemical method is 3.68%, and protein content is 3.33%, and density is 1.026, approaching with the average data of the used fresh breast of experiment, can eliminate the differentiation distortion as a result that causes because of content difference.
(3) preparation of different gradient recombined milks: according to recombined milk concentration is 0,10%, 20%, 33%, 50%, 66%, 80%, 100% gradient, carries out the preparation of fresh breast and recombined milk.Obtain altogether to comprise 8 kinds of the different gradient laboratory samples of fresh breast, 15 every kind, 120 of total number of samples.
2. near infrared spectra collection
With sample constant temperature to 40 ± 0.1 ℃, use Fourier transform near infrared spectrometer (U.S. ThermoNicolet company produces, model ANTARIS) then, the diffuse reflection spectrum of associative multiplication bulb separation annex collected specimens, detecting wavelength coverage is 800～2500nm, is spaced apart 2nm.Earlier pour sample into diameter 2cm during each the collection, in the cylindrical sample cup of high 5cm, then sample cup being placed hot spot is on the integrating sphere of 0.9cm.Each sample collecting three times scans 64 times at every turn and averages, by the computer recording absorbance that links to each other.
3. set up the quantitative identification model:
(1) data processing: select the full spectrum of 800～2500nm to set up model, utilize methods such as polynary scatter correction processing, standard normal conversion, first derivation, second order differentiate and multiple spot are level and smooth successively spectroscopic data to be optimized processing, and the graph of a relation rejecting abnormalities sample of chemical score tization residual error and mahalanobis distance value per sample, these data processing all utilize TQAnalyst V6.2 process software (U.S. ThermoNicolet company) to carry out;
(2) set up model: utilize partial least square method, set up the relational model between sample concentration and the near infrared spectrum.Utilize related coefficient (R), model standard deviation (RMSECV) to come the quality of judgment models then, up to the model that obtains R maximum, RMSECV minimum.
It is 0.971 that this experiment obtains related coefficient, and the model standard deviation is 7.76% quantitative identification model.
4. make quantitative identification: adopt the described method of step 2 that unknown sample is gathered near infrared spectrum, adopt (1) described method of step 3 to carry out data processing, then the optimization spectroscopic data of unknown sample is brought into the quantitative identification model of foundation, utilized TQ Analyst V6.2 process software to calculate the amount of recombined milk in the unknown sample.
Identification result is: the result that the amount of recombined milk and chemical method record in the unknown sample that calculates is very approximate, shows that this method is fit to practical application.
Claims (9)
1, a kind of method of utilizing near infrared spectrum to differentiate the recombined milk in fresh breast and commodity Ruzhong, it may further comprise the steps:
(1) pre-treatment of sample;
(2) near infrared spectra collection of sample;
(3) set up qualitative or the quantitative identification model;
(4) unknown sample is gathered near infrared spectrum, utilize the model of setting up in the step (3), carry out data processing, make qualitative or quantitative identification.
2, method according to claim 1, it is characterized in that described sample pre-treatments is: fresh breast or commodity breast is mixed with recombined milk, be mixed with recombined milk concentration and be respectively 0,10%, 20%, 33%, 50%, 66%, 80%, 100% sample.
3, method according to claim 1, the near infrared spectra collection that it is characterized in that sample are with sample constant temperature to 40 ± 0.1 ℃, use the spectrum of near infrared spectrometer collected specimens then, and detecting wavelength coverage is 800～2500nm, is spaced apart 2nm.
4, method according to claim 1 is characterized in that the foundation of qualitative discrimination model may further comprise the steps:
(1) data processing: the characteristic wave bands of one or more among the full spectrum of selection 800～2500nm or 900～1000nm, 1000～1200nm, the 1100～2500nm is set up model, utilize methods such as polynary scatter correction processing, standard normal conversion, first derivation, second order differentiate and multiple spot are level and smooth that spectroscopic data is optimized processing, and the graph of a relation rejecting abnormalities sample of chemical score tization residual error and mahalanobis distance value per sample;
(2) set up model: the spectroscopic data matrix to samples of different concentrations carries out principal component analysis (PCA) respectively, sets up the principal component analysis (PCA) mathematical model.
5, method according to claim 4, when it is characterized in that unknown sample made qualitative identification, optimization spectroscopic data with unknown sample carries out the major component decomposition earlier, in the major component space of each class, carry out the mahalanobis distance computing, obtain the distance of each class sample, utilize the qualitative discrimination model of building to handle, draw identification result.
6, method according to claim 4 is characterized in that utilizing recombined milk at 1890～1898nm characteristic peak to be arranged, and fresh breast has the difference of characteristic peak at 1880～1888nm, and directly the second derivative figure according to spectrum makes qualitative identification.
7, method according to claim 1 is characterized in that the foundation of quantitative identification model may further comprise the steps:
(1) data processing: the characteristic wave bands of one or more among the full spectrum of selection 800～2500nm or 900～1000nm, 1000～1200nm, the 1100～2500nm is set up model, utilize means such as polynary scatter correction processing, standard normal conversion, first derivation, second order differentiate and multiple spot are level and smooth that spectroscopic data is optimized processing, and the graph of a relation rejecting abnormalities sample of chemical score tization residual error and mahalanobis distance value per sample;
(2) set up model: utilize partial least square method, set up the relational model between sample concentration and the near infrared spectrum.
8, method according to claim 7 is characterized in that the related coefficient of the quantitative identification model set up is 0.971, and the model standard deviation is 7.76%.
9, according to claim 7 or 8 described methods, when it is characterized in that unknown sample made quantitative identification, bring the optimization spectroscopic data of unknown sample the quantitative identification model of foundation into, utilize TQ AnalystV6.2 process software to calculate the content of recombined milk in the unknown sample.
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