CN102252995A - Method for rapid detection and authenticity identification of fatty acid of racy camellia oil by near infrared transmission spectroscopy (NITS) - Google Patents
Method for rapid detection and authenticity identification of fatty acid of racy camellia oil by near infrared transmission spectroscopy (NITS) Download PDFInfo
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Abstract
The invention discloses a method for rapid detection and authenticity identification of fatty acid of racy camellia oil by near infrared transmission spectroscopy (NITS). The method comprises the steps of: screening high quality varieties with oil content of 30%-60% from more than 130 camellia seed varieties, wherein in the camellia oil, the content of oleinic acid is 65%-85%, the content of linoleic acid is 5%-20%, the content of palmitic acid is 3%-15%, and the content of stearic acid is 1%-5%; establishing a near infrared transmission spectroscopy (NITS) model of the main fatty acids (oleinic acid, linoleic acid, palmitic acid, stearic acid and total unsaturated fatty acid) with a partial least squares (PLS) method by adopting the Fourier near infrared transmission spectroscopy (NITS), wherein the determination coefficients of the correction models of the oleinic acid, the linoleic acid and the palmitic acid respectively are 0.93446, 0.96538 and 0.88789, and the determination coefficients of cross validation respectively are 0.91987, 0.95755 and 0.84447; further verifying accuracy and reliability of five NIRS (Near Infrared Reflectance Spectroscopy) models by external verification so as to obtain related coefficients of the external verification, which respectively are 0.9424, 0.9682, 0.8862, 0.6834 and 0.7587; and evaluating doped camellia oil by establishing the NIRS model of binary system miscella of the camellia oil. The method is applicable to rapid measurement of the content of main fatty acids of the camellia oil and the doped camellia oil, has the characteristics of simplicity, convenience, rapidness and economy, and is suitable for industrial application.
Description
Technical field
The present invention relates to edible vegetable oil attributional analysis field, particularly a kind of near-infrared transmission spectrum fast detecting original flavor tea oil fatty acid and false distinguishing method.
Background technology
Oil tea is the distinctive good indigenous tree of China.It is listed as the world four big woody oleiferous plants plants with olive, oil palm, coconut.Tea oil is to advocate the edible oil of promoting in " Chinese eating patterns reform and development planning outline " energetically, also is the first-elected health care vegetable edible oil of international food and agricultural organization.Tea oil mainly is made up of oleic acid, linoleic acid and a spot of saturated fatty acid, and its composition is similar to the olive oil that is called as " vegetable oil queen ", and unsaturated fatty acid content is up to more than 90%, and wherein oleic acid content is up to more than 70%.According to American National medicine center experiment confirm: tea oil is claimed " long life oil " in the world to reducing cholesterol and anticancer certain effect being arranged.Tea oil also has medical value in addition." Chinese pharmacopoeia is recorded tea oil as medicinal oil.
Tea oil is very useful to health, and the market price is constantly high.In Japan, the tea oil price is 7.5 times of rapeseed oil.In China Hong Kong and Taiwan area and every country in Southeast Asia, the tea oil after the refining has become the elderly's easy-to-sell goods and daily necessities.But along with the raising of people's living standard and the reinforcement of health care consciousness, the increase of tea oil demand, adulteration appears in the tea oil on the market, as soybean oil, rapeseed oil, palm oil are mixed tea oil etc., influences the former of tea oil and has good taste and nutritional character.Country's camellia seed oil standard (GB11765-2003) has been made regulation to quality index such as the color and luster of tea oil, smell, acid value, peroxide values, but because the similarity of physicochemical characteristic between the vegetable oil, can't differentiate effectively that tea oil mixes puppet.Lack at present original flavor oil tea qualitative characteristics and authentication detection technology research fast, set up practical, mix pseudo-the discriminating and the method for attributional analysis accurately, be to the consumer or all be very important concerning law enforcement agency.
The quality of oil comprises sensory evaluation, physical chemical characteristics and the security of oil.At present, about the pseudo-discrimination method of mixing of tea oil mainly is by organoleptic examination and physico-chemical method that some are conventional, as measure relative density, solidifying point, specific heat, refraction index, iodine number etc., but because the similarity of physicochemical characteristic between the vegetable oil, these methods are always ineffective, and selectivity is poor.Bibliographical information adopts the composition of fatty acid in the capillary gas chromatography tea oil, and this method time is long, and complex operation has been difficult to satisfy modern grease check needs.
Near-infrared spectrum technique (NlRS) has been with fastest developing speed since the nineties in 20th century, one of the most noticeable green analytical technology, be specially adapted to breeding and in early days the quality of a large amount of each generation material carried out express-analysis and screening, thought the method for " have and solve global agricultural analysis potentiality " by international agricultural analysis circle, be widely used in the analyzing and testing of grease, agricultural product and food quality etc.Near infrared spectroscopic method has been widely used in the express-analysis of vegetable oil oleaginousness and fatty acid composition, such as rapeseed oil, soybean oil, corn oil, cottonseed oil, sunflower oil, sesame wet goods, can apply to the requirement of the extensive fast detecting of these vegetable oil breedings and attributional analysis basically.But still do not use the method to analyze the related chemical constituents of tea oil both at home and abroad at present.
Near infrared spectrum can be divided into two kinds of near-infrared transmission spectrum (NIT) and reflectance spectrums (NIR) according to its detected object difference.Transmitted spectrum (short wavelength regions in) is meant testing sample placed between light source and the detecting device, the only transmitted light that detecting device detected or interact with sample molecule after light (having carried sample structure and composition information).This spectral technique is mainly used in the detection of thorough fluid sample, and quantitative test is according to Beer law E=-log (I
Trans/ I
0The logT=ε cd of)=-(ε: extinction coefficient, c: concentration, d: light path).If sample is muddy, or has in the sample and can produce the particulate matter of scattering, or light distance of process in sample is uncertain that relation between this moment transmitted intensity and the sample concentration does not meet the Beer law to light.Should use the diffuse transmission analytic approach to this sample, quantitative test is according to law E=-log (I
Scatt/ I
0The logR=k ε c of)=-(ε: extinction coefficient, c: concentration, k: scattering coefficient).Reflectance spectrum (Long wavelength region in) is meant the same side that detecting device and light source is placed sample, and what detecting device detected is the light that sample reflects in every way.Use the degree of grinding unanimity that requires sample when diffuse feflectance spec-troscopy is analyzed, thereby guarantee the smooth unanimity of sample surfaces.This spectral technique is mainly used in the detection of granule solid and powdered sample.
Near infrared spectroscopy is aspect the oil product authentication detection technology, and most research mainly is to launch mixing of olive oil is pseudo-, and the research of tea oil being mixed pseudo-detection is less relatively.The father-in-law is joyful to wait the people to study to mix in the olive oil sesame oil, soybean oil, sunflower oil to mix pseudo-situation, adopt the BP neural network to mixing pseudo-olive oil and not mixing pseudo-olive oil and differentiate, 52 samples are predicted, predictablity rate is 100%, also set up simultaneously and mixed the PLS model that pseudo-oily binary system mixes oil content, the related coefficient that this model is measured sesame oil, soybean oil and sunflower oil is 99.77%, 99.37%, 99.44%.Yang etc. adopt infrared spectrum, near infrared spectrum and 3 kinds of methods of Raman spectrum that olive oil is mixed puppet simultaneously and study, and mix pseudo-weight range from 0% to 100%, and the coefficient of determination of the model of being set up is all more than 0.99.Li Wang utilizes attenuated total reflection infrared spectrum and optical fiber diffuse reflection near infrared spectrum to analyze mixing mingling of soybean oil in the tea oil, and set up the near infrared light spectrum model that adopts partial least square method, its related coefficient is 0.992, and its predicted results is fine.
This patent is by analyzing domestic and international research to tea oil and association area, setting up on the characteristic spectrum basis of different cultivars tea oil, using near-infrared spectrum technique sets up the constituent analysis of high-quality original flavor edible camellia oil and mixes pseudo-discrimination method fast, for the processing of oil tea grease provides technical support, for tea oil quality evaluation and Quality Control Technology thereof provide foundation, it is the demand that ensures original flavor tea oil quality, and will open up the exploitation of functional evaluation of tea oil polyphenoils and new product thereof, thereby help the expansion of tea oil industry and the assurance of national health.
Summary of the invention
Country's camellia seed oil standard (GB11765-2003) has been made regulation to quality index such as the color and luster of tea oil, smell, acid value, peroxide values, but because the similarity of physicochemical characteristic between the vegetable oil, can't differentiate effectively that tea oil mixes puppet.Lack original flavor tea oil qualitative characteristics and quick authentication detection technology at present, the object of the present invention is to provide a kind of near-infrared transmission spectrum fast detecting original flavor tea oil fatty acid and false distinguishing method.This method is not only simple and convenient, and economic environmental protection is effective, is fit to tea oil process and and the detection of original flavor tea oil mass marketed cost.Its technical scheme and route such as Fig. 1.
Technical solution of the present invention is to adopt Fourier's near-infrared transmission spectral analysis technique to measure the content of oleic acid in the different cultivars tea oil, linoleic acid, palmitic acid, stearic acid and total unsaturated fatty acid, and differentiate fast and mix other edible vegetable oil in the tea oil, form by following steps:
The screening of first step high-quality oil tea kind
The screening oil content is at the fine quality of 30%-60% from more than 130 tea seed kinds, oleic acid content 65%-85% wherein, linoleic acid content 5%-20%, palmitic acid content 3%-15%, stearic acid content 1%-5%;
The foundation of second step each fatty acid NITS model of tea oil
Gather 90-140 different tea oil samples, be divided into 90-110 modeling sample collection and 20-30 verification sample collection, measure spectrum scope 4000-12000cm
-1, scanning times is 64 times, resolution is 16cm
-1, 2 multiplication benefits.Adopt the PRESS function, reject the difference value, adopt optimal spectrum preprocess method, main cause subnumber, spectral band, obtain the near-infrared model of the content of oleic acid, linoleic acid, palmitic acid, stearic acid and total unsaturated fatty acid respectively, it proofreaies and correct the coefficient of determination at 0.9999-0.7000, and the cross validation coefficient of determination is at 0.9999-0.6500;
The external certificate of the 3rd step each fatty acid NITS model of tea oil
NITS model by tea oil fatty acid detects unknown sample, GC assay value and predicted value is compared, and draw corresponding relation figure, the external certificate coefficient R
2Be respectively 0.6800-0.9950;
The preparation of the 4th step binary system miscella
In tea oil and other edible vegetable oil mass percent is 1: 0-1.5 (ratio of mingling is 0-60%), prepare 50-80 miscella sample, and all sample is divided into two parts, calibration set 50-60 and inspection set 10-20;
The foundation that the 5th step was mixed pseudo-tea oil NITS model
Adopt Fourier's near-infrared transmittance, be applied to the miscella binary system sample of different proportion, with the best preprocess method of " second derivative+Norrisderivative filter " and the homing method of PLS, set up the quantitative NITS model of other food plant oil content that mixes in the fast detecting tea oil, to the quantitative test at random of miscella sample;
The evaluation that the 6th step was mixed pseudo-tea oil NITS model
NITS model by tea oil binary system miscella detects unknown sample, actual value and NITS model predication value is compared gained external certificate coefficient R
2Be respectively 0.6800-0.9999, doping tea oil is estimated.
The present invention is in order to set up the distinctive characteristic spectrum of original flavor tea oil, the screening content of fatty acid is concentrated the kind of representing original flavor tea oil feature from more than 130 kind in the different places of production, adopt oleic acid, linoleic acid, palmitic acid, stearic content in the gas chromatographic analysis different cultivars tea oil, fatty acid standard items and tea oil sample GC characteristic pattern such as Fig. 2.The GC chromatographic column is selected SE-30 for use, flame ionization ditector (FID), and 280 ℃ of injector temperatures, 280 ℃ of detector temperatures, 200 ℃ of column temperatures continue 5min, are warming up to 270 ℃ with the speed of 5 ℃ of per minutes, continue 1min.Obtain different fatty acid GC characteristic spectrums and content in the original flavor tea oil, the unsaturated fatty acid total amount is greater than 85%, oleic acid content 65%-85% wherein, and linoleic acid content 5%-20%, palmitic acid content 3%-15%, stearic acid content are 1-5%.
Calculate according to formula w=m with different cultivars tea seed oil content among the present invention
1/ m
0* 100%.Wherein w is an oil content, m
1Be the tea oil weight of tea seed after sherwood oil extracting gained extract steams empty concentrating, m
0For not extracting tea seed weight.The present invention adopts cable-styled extraction method, with the plant comminutor tea seed is ground into Powderedly, takes by weighing a certain amount of tea seed, puts it in the filtration paper cylinder, and absorbent cotton is filled in top, compresses sample, puts into extractor.Add the sherwood oil refluxing extraction in the extracting bottle, extraction agent is sherwood oil (60 ℃-90 ℃), and solid-to-liquid ratio is 1: 10-40 (g/mL), extract 70 ℃-95 ℃ of temperature, extraction time 4-10h.Different cultivars tea seed oil content such as table 1 (sample No. 1 to No. 120 from Jiangxi).
The oil content of table 1 different cultivars tea seed
This patent is found (seeing Table 1) to the mensuration of the 132 kinds of tea seed oil contents in ground such as Yunnan, Guangxi, Jiangxi, and different cultivars tea seed oil content exists than big-difference.Oil content is having 26 kinds below 30%, 30% to 40% has 27 kinds, and 40% to 50% has 60 kinds, and 19 kinds are arranged more than 50%.What wherein oil content was minimum is No. 117 samples in Jiangxi, only is 0.60%; The highest is No. 69 samples in Jiangxi, is 57.96%.And its oil content major part all concentrates between 30% to 60%, and average oil content is 38.39%.Because the oil content of different cultivars tea seed exists than big-difference, and the proportion of tea oil directly has influence on the prospect that it is developed in edible oil market, selecting excellent kind of oil tea product of high oil mass to tie up to has crucial effect in its industrialization process.Therefore, this patent screens the fine quality of oil content at 30%-60% from more than 130 tea seed kinds.
110 kinds of samples that this patent will collect are divided into 90 modeling sample collection and 20 verification sample collection, analyze maximal value, minimum value, average, the standard deviation of its various content of fatty acid.Mainly contain fatty acid compositions such as oleic acid, linoleic acid, palmitic acid, stearic acid in the tea oil, also have squalene, vitamin E isoreactivity material, these materials all have groups such as common C-H, O-H, have very strong absorption in the near infrared spectrum zone.As seen from Figure 3, the near infrared light spectrogram of tea oil has tangible absorption peak in many places, and the absorption peak strength difference of different samples, i.e. content difference.Collection of illustrative plates is at 6000-5500cm
-1, 4500-4000cm
-1There is very strong absorption at the place, can be used as the feature of tea oil collection of illustrative plates.4500cm
-1About be-CH
3,-CH
2Absorb with the sum of fundamental frequencies of the stretching vibration of C-H.4700cm
-1About relevant with the sum of fundamental frequencies of C-H and C=O stretching vibration, 5800cm
-1About be-CH
3,-CH
2, the C-H stretching vibration among the HC=CH-the one-level frequency multiplication absorb, at 8250cm
-1Near the secondary frequency multiplication that the wave number is the C-H stretching vibration absorbs 7100cm
-1One-level frequency multiplication absorption for the O-H stretching vibration.In addition, tea oil and other plant oil have evident difference, as shown in Figure 4.The tea oil binary system promptly mixes other vegetable oil, and as palm oil, soybean oil, rapeseed oil and corn wet goods, the preferred soybean oil of the present invention carries out near-infrared spectrum analysis as the binary system miscella.This is the foundation that the near infrared light spectrogram can be used as quantitative test tea oil content of fatty acid and false distinguishing.
This patent can adopt the PRESS function in the NITS modeling, reject the difference value, obtains the modeling number of the near-infrared model of different chemical composition.The SD of oleic acid and linoleic calibration set is respectively 3.1351 and 2.4452, and coverage is bigger, has good representativeness, can predict unknown sample well.The SD of the calibration set of palmitic acid and unsaturated fatty acid is 1.0896 and 1.0381, predicts unknown sample preferably.
This patent adopts first order derivative and second derivative method in the selection of optimal spectrum preprocess method, use Savitzky-Golay filter and Norris derivative filter method that derivative spectrum is carried out smoothing processing, with R
CvWith the RMSECV index as the model evaluation standard.This patent adopts determined optimal spectrum preprocess method, main cause subnumber, spectral band, has set up the NITS analytical model of tea oil oleic acid, linoleic acid, palmitic acid, stearic acid and five kinds of compositions of unsaturated fatty acid respectively.The best preprocess method of near-infrared transmission spectrum (NITS) model of oleic acid that this patent is built is single order+SG, R
cWith RMSEC be 0.93446 and 1.09, R
CvWith RMSECV be 0.91987 and 1.21.The best pretreatment mode of linoleic NITS model is second order+SG, R
cWith RMSEC be 0.96538 and 0.634, R
CvWith RMSECV be 0.95755 and 0.701.The best preprocess method of the NITS model of palmitic acid is single order+SG, R
cWith RMSEC be 0.88789 and 0.498, R
CvWith RMSECV be 0.84447 and 0.582.Its best preprocess method of stearic NITS model is second order+Nd, R
cWith RMSEC be 0.73378 and 0.380, R
CvWith RMSECV be 0.69114 and 0.405.The best preprocess method of the NITS model of unsaturated fatty acid is a second order, R
cWith RMSEC be 0.78823 and 0.635,
R
CvWith RMSECV be 0.67440 and 0.771.
This patent has been set up the external certificate method of each fatty acid near-infrared model of tea oil.Carry out external inspection with the near infrared light spectrum model of having set up, unknown sample is carried out stochastic analysis, GC assay value and NITS predicted value are carried out linear ratio, obtain coefficient R separately
2The external certificate result that this patent is set up the NITS model to oleic acid, linoleic acid, palmitic acid, stearic acid, unsaturated fatty acid in the tea oil has certain difference, the R of oleic acid, linoleic acid, palmitic acid
2Reach 0.9424,0.9682,0.8862, illustrate that the predicted value of these three kinds of compositions and chemical score have good correlativity, predictive ability is stronger.The R of stearic acid and unsaturated fatty acid
2Be respectively 0.6834,0.7587, illustrate that this NITS model can not accurately predict these two kinds of compositions of tea oil sample well.The ability size of its utilization NITS model express-analysis unknown sample is linoleic acid＞oleic acid＞palmitic acid＞unsaturated fatty acid＞stearic acid.
This patent adopts Fourier's near-infrared transmittance, be applied to mix the tea oil binary system sample of different proportion soya-bean oil, by the optimization of various preprocessing procedures and homing method, set up the near infrared spectrum quantitative model of other content of vegetable oil that mixes in the fast detecting tea oil.With homing method institute established model the best of the best preprocess method and the PLS of " second derivative+Norris derivative filter ", it proofreaies and correct related coefficient (R
c) and calibration standard error (RMSEC) be respectively 0.99999,0.05770; Crosscheck related coefficient (R
Cv) and crosscheck calibration error (RMSECV) be 0.99999,0.0719; Optimum wave band is 5037.16～4728.60cm
-1, 7852.72～7089.04cm
-1, 8577.82～8323.26cm
-1Best main cause subnumber is 6.In addition, get the NITS predicted value of 15 parts of chance samples and the related coefficient (R of chemical score through external certificate
2) be 0.998.Show that the quantitative test quickly and accurately of near-infrared transmission spectroscopic methodology mingles the content of other vegetable oil in the tea oil.
The binary system miscella is the miscella of any formation in tea oil and other edible vegetable oil (palm oil, soybean oil, rapeseed oil and corn oil) in this patent.This patent is when the tea oil binary system miscella of preparation different proportion (mass ratio), and scope is in the 0-60% gradient.50-80 sample is set, and all sample is divided into two parts, calibration set 45-60 and inspection set 10-20.This patent method not only is suitable for the false distinguishing of tea oil binary system miscella, and the multicomponent system miscella that forms of other edible vegetable oil that is suitable in the tea oil mixing false distinguishing, but other edible vegetable oil ratio of mixing is less than 60%.
The present invention obtains following technique effect:
1. propose near infrared spectroscopic method first and analyze the tea oil content of fatty acid apace, obtained the NITS model of oleic acid, linoleic acid, palmitic acid, stearic acid and unsaturated fatty acid by different preprocessing procedures, the NITS model that uses each fatty acid to set up has carried out fast detecting to unknown sample, obtains oleic acid and linoleic R
2Reach 0.9424 and 0.9682, can predict actual sample exactly.
2. adopt Fourier's near-infrared transmittance first, be applied to the tea oil binary system sample of different proportion, set up the quantitative model of the near infrared spectrum of other content of vegetable oil that mixes in the fast detecting tea oil.With homing method institute established model the best of the best preprocess method and the PLS of " second derivative+Norris derivative filter ", it proofreaies and correct related coefficient (R
c) be 0.99999, crosscheck related coefficient (R
Cv) be 0.99999, optimum wave band is 5037.16～4728.60cm
-1, 7852.72～7089.04cm
-1, 8577.82～8323.26cm
-1Best main cause subnumber is 6.
3. the NITS of the inventive method foundation analyzes the model of mingling the tea oil binary system, through the related coefficient (R of the NITS of external certificate chance sample predicted value and chemical score
2) be 0.998, have good linear relationship, credit is analysed by statistics, and the predicted value and the actual value of NITS model carried out Paired Samples Test, and the t value is 0.659, and p=0.521＞0.05 does not have significant difference.Therefore, the present invention sets up the content that other vegetable oil in the tea oil is mingled in the quantitative test quickly and accurately of near-infrared transmission spectroscopic methodology.
4. this patent method not only is suitable for the false distinguishing of tea oil binary system miscella, and is suitable for the many of other edible vegetable oil formation that mix in the tea oil
Unit's system miscella false distinguishing, but other edible vegetable oil ratio of mixing is less than 60%.
Description of drawings
The technical scheme and the route of accompanying drawing 1 near infrared spectrum false distinguishing tea oil
The GC characteristic pattern of accompanying drawing 2 fatty acid standard items and tea oil sample
The near infrared light spectrogram of accompanying drawing 3 original flavor tea oil
The near infrared light spectrogram of accompanying drawing 4 original flavor tea oil and soya-bean oil
The oil content distribution plan of accompanying drawing 5 different cultivars tea seeds
Oleic acid, linoleic acid, palmitic acid, stearic content in the accompanying drawing 6 different cultivars tea oil
The external certificate figure of the near infrared light spectrum model of accompanying drawing 7 various fatty acid
Accompanying drawing 8 is mixed the correction chart and the cross validation figure of pseudo-tea oil NITS model
The external certificate of the tea oil near infrared light spectrum model of accompanying drawing 9 doping soya-bean oil
Embodiment
Following examples are more of the present invention giving an example, and should not regarded as limitation of the invention.
A kind of near-infrared transmission spectrum (NITS) fast detecting original flavor tea oil fatty acid and false distinguishing method, the content that it is characterized in that oleic acid, linoleic acid, palmitic acid, stearic acid and total unsaturated fatty acid in Fourier's near-infrared transmission spectral analysis technique mensuration different cultivars tea oil, and differentiate fast and mix other edible vegetable oil in the tea oil, form by following steps:
The screening of first step high-quality oil tea kind
The screening oil content is at the fine quality of 30%-60% from more than 130 tea seed kinds, oleic acid content 65%-85% wherein, linoleic acid content 5%-20%, palmitic acid content 3%-15%, stearic acid content 1%-5%;
The foundation of second step each fatty acid NITS model of tea oil
Gather 90-140 different tea oil samples, as 90,100,110,120,130 and 140 product samples, modeling sample collection are 90-110, as 90,95, and 98,100,105,110, verification sample collection 20-30, as 20,22,25,28,30 etc.Selective light spectral limit 4000-12000cm
-1, scanning times is 64 times, resolution is 16cm
-1, 2 multiplication benefits.Adopt the PRESS function, reject the difference value, adopt optimal spectrum preprocess method, main cause subnumber, spectral band, obtain the near-infrared model of the content of oleic acid, linoleic acid, palmitic acid, stearic acid and total unsaturated fatty acid respectively, it proofreaies and correct coefficient of determination R
cBe 0.9999-0.7000, preferred 0.9999-0.9950, cross validation coefficient of determination R
CvBe 0.9999-0.6500, preferred 0.9999-0.9950;
The external certificate of the 3rd step each fatty acid NITS model of tea oil
NITS model by tea oil fatty acid detects unknown sample, predicted value and GC assay value is compared, and draw corresponding relation figure, the external certificate coefficient R
2Be respectively 0.6800-0.9950, preferred 0.9900-0.9950;
The preparation of the 4th step binary system miscella
In tea oil and other edible vegetable oil mass percent is 1: 0-1.5 (ratio of mingling is 0-60%), preferred 1: 0-0.5.Prepare 50-80 miscella sample, as 50,55,60,65,68,70,75,80 etc., all sample is divided into two parts, calibration set 50-60 and inspection set 10-20;
The foundation that the 5th step was mixed pseudo-tea oil NITS model
Adopt Fourier's near-infrared transmittance, be applied to the miscella binary system sample of different proportion, with the best preprocess method of " second derivative+Norrisderivative filter " and the homing method of PLS, set up the quantitative NITS model of other food plant oil content that mixes in the fast detecting tea oil, to the quantitative test at random of miscella sample;
The evaluation that the 6th step was mixed pseudo-tea oil NITS model
NITS model by tea oil binary system miscella detects unknown sample, actual value and NITS model predication value is compared the external certificate coefficient R
2Be respectively 0.6800-0.9950, preferred 0.9900-0.9950 estimates doping tea oil.
Oil content is measured and is adopted cable-styled extraction method in present embodiment step 1, and extraction agent is sherwood oil (60 ℃-90 ℃), and solid-to-liquid ratio is 1: 10-40 (g/mL), and preferred 1: 30-40 (g/mL), extract 70 ℃-95 ℃ of temperature, extraction time 4-10h.
The assay of oleic acid, linoleic acid, palmitic acid, stearic acid and total unsaturated fatty acid adopts GC in present embodiment step 1, chromatographic column is selected SE-30 for use, flame ionization ditector (FID), 280 ℃ of injector temperatures, 280 ℃ of detector temperatures, 200 ℃ of column temperatures continue 5min, speed with 5 ℃ of per minutes is warming up to 270 ℃, continues 1min.
The binary system miscella is the miscella of any formation in tea oil and other edible vegetable oil (palm oil, soybean oil, rapeseed oil and corn oil) in present embodiment step 4.The ratio of other a kind of edible vegetable oil of doping is less than 60% in the tea oil.
The tea seed of drying is ground into Powdered (contain kind of a benevolence shell, the sample water percentage is lower than 10%), takes by weighing a certain amount of tea seed powder, record weight m
0Put it in the filtration paper cylinder, absorbent cotton is filled in top, compresses sample, puts into extractor.Add sherwood oil (60 ℃-90 ℃) 180mL in the extracting bottle, 80 ℃ are extracted 6h down, and extract promptly gets tea oil after steaming empty concentrated solvent, claim oil heavy m
1Calculate the oil content w=m of corresponding kind
1/ m
0
Present embodiment is selected Yunnan, Jiangxi, zhejiang and other places different cultivars, result such as table 2 and Fig. 5.Different cultivars tea seed oil content is having 26 kinds below 30%, 30% to 40% has 27 kinds, and 40% to 50% has 60 kinds, and 19 kinds are arranged more than 50%.What wherein oil content was minimum is No. 117 samples in Jiangxi, only is 0.60%; The highest is No. 69 samples in Jiangxi, is 57.96%.And its oil content major part all concentrates between 30% to 60%, and average oil content is 38.39%, and standard deviation is 13.80.Coming preceding 10 kind is 69,88,13,12,118,74,100,10,86, No. 70 samples in Jiangxi.The oil content of different cultivars tea seed is obviously different, may confidential relation be arranged with not equal subjectivity of local climate, seed variety and planting type and objective factor.
Fatty acid is formed in the embodiment 3 gas Chromatographic Determination different cultivars tea oil
Sample according to embodiment 2 preparations carries out the esterification pre-service to sample.The kind that present embodiment is selected has Guangxi (reach the clouds, in Liuzhou melt water, anti-city field, Baise, Fengshan, Rong'an, Tianyang County, Nandan, common oil tea), spends tea oil in vain, safflower tea oil, the rich peaceful Expansive in Yunnan towards and 129 samples (as table 2) such as Jiangxi 1-120 kind sample, other gets 9 safflower oil teas of Yunnan Tengchong sample.Get the tea oil sample and drip on a small quantity in the 10mL test tube, add 2mL 0.5mol/L NaOH-CH
3OH shakes up, and puts into esterification 30min in 60 ℃ of water-baths, takes out to add the 5mL normal hexane again, shakes up, and leaves standstill the back and takes out supernatant liquor, carries out the GC stratographic analysis.
The GC analysis condition: chromatographic column is selected SE-30 for use; Flame ionization ditector (FID); 280 ℃ of injector temperatures, 280 ℃ of detector temperatures, 200 ℃ of column temperatures continue 5min, are warming up to 270 ℃ with the speed of 5 ℃ of per minutes, continue 1min.Sample size: 1 μ L.
By to fatty acid compositional analysis in 129 kinds of oil tea strains in Jiangxi and Guangxi and the Yunnan safflower oil tea kind, composition and the content of finding each kind have very big difference, but the fatty acid of tea oil is made up of 4 kinds of fatty acid such as palmitic acid, stearic acid, oleic acid and linoleic acid substantially, and it is content distribution such as Fig. 6 separately.The content of oleic acid is at 70.33%-86.21%, and average is 78.24%; Linoleic content is at 3.25%-17.18%, and average is 9.50%; Palmitic acid is the maximum saturated fatty acid of content in the tea oil, and content is at 7.03%-13.85%, and average is 9.63%; Stearic content is at 1.35%-5.49%, and average is 2.61%.And the oleic acid content of safflower oil tea is at 63%-75%, and linoleic acid is at 8%-16%,, palmitic acid is at 12%-15%, stearic acid 1%-5%.The result is as table 2-3.
The statistics (%) of the various content of fatty acid of 129 kinds of tea oil such as table 2 Guangxi, Jiangxi Province
The fatty acid of table 3 Yunnan safflower tea oil sample is formed content (%)
Embodiment 4 near-infrared transmission spectroscopic methodology express-analysis tea oil content of fatty acid
1) GC analyzes the fatty acid composition of different cultivars tea oil
According to the sample of embodiment 2 preparation, all get each sample 2-3 and drip and put into the test tube bottom, add 2.0mL 0.5molL
-1Sodium methoxide solution shakes up, and 60 ℃ of water-bath 30min add the 5mL normal hexane then, and fully mixing leaves standstill a moment.After treating the solution layering, get upper solution air inlet facies analysis.The gas phase analysis condition is with embodiment 2.
2) the near-infrared transmission spectra collection of tea oil sample
The sample of embodiment 2 preparations is put into sample bottle 2/3 place get final product spectrum to be scanned.Start shooting and made the instrument preheating in 1 hour.Before gathering spectrum, use RESULT-Integration software programming spectra collection program earlier, Instrument working parameter is set.Measure spectrum scope 4000-12000cm
-1, scanning times is 64 times, resolution is 16cm
-1, 2 multiplication benefits.Sample mode is tranmittance; Data collection form is absorbance.Directly sample is carried out the collection of near infrared spectrum after finishing capture program.Each sample scans 3 times from different perspectives, and each all scanning backgrounds calculate its averaged spectrum, preserve, and are to be analyzed.
3) each fatty acid NITS model optimal spectrum preprocess method of tea oil determines
Mainly contain fatty acid such as oleic acid, linoleic acid, palmitic acid, stearic acid in the tea oil, at 6000-5500cm
-1, 4500-4000cm
-1There is very strong absorption at the place, can be used as the feature of tea oil collection of illustrative plates.To the data of near-infrared transmission spectra collection in the step 2, use Savitzky-Golay filter and Norris derivative filter method that derivative spectrum is carried out smoothing processing.Adopt determined optimal spectrum preprocess method, main cause subnumber, spectral band, set up the NITS analytical model of tea oil oleic acid, linoleic acid, palmitic acid, stearic acid and five kinds of compositions of unsaturated fatty acid respectively.The result is as table 4-8.
The different preprocessing procedures of table 4 is to the influence of the near-infrared model of oleic acid in the tea oil
The different preprocessing procedures of table 5 is to the influence of linoleic near-infrared model in the tea oil
The different preprocessing procedures of table 6 is to the influence of the near-infrared model of palmitic acid in the tea oil
The different preprocessing procedures of table 7 is to the influence of stearic near-infrared model in the tea oil
The different preprocessing procedures of table 8 is to the influence of the near-infrared model of unsaturated fatty acid in the tea oil
Utilize TQ Analyst 8 spectral manipulation softwares to carry out spectrum pre-service, the selection of spectrum district and regression statistical analysis.Adopt the correcting sample collection to set up calibration model, automatically select optimum spectral range by software, and use various preprocessing procedures to model optimization, such as multicomponent signal correction (Multiplicative signal correction is arranged, MSC), standard canonical transformation (Standrad normal variate, SNV), first order derivative (First derivative, 1
StDeriv.), second derivative (Second derivative, 2
NdDeriv.), Savitzky-Golay smoothing processing and Norris smoothing processing etc.Moreover, use internal chiasma proof method and external certificate model is verified.During Optimization Model with the correction related coefficient (R of model
c), crosscheck related coefficient (R
Cv), calibration standard error (RMSEC), crosscheck calibration error (RMSECV), external inspection related coefficient (R
2) wait as the important indicator of weighing the model quality.
The best preprocess method of oleic acid near infrared spectrum (NITS) model that present embodiment is built is single order+SG., R
cWith RMSEC be 0.93446 and 1.09, R
CvWith RMSECV be 0.91987 and 1.21.The best pretreatment mode of linoleic NITS model is second order+SG, R
cWith RMSEC be 0.96538 and 0.634, R
CvWith RMSECV be 0.95755 and 0.701.The best preprocess method of the NITS model of palmitic acid is single order+SG, R
cWith RMSEC be 0.88789 and 0.498, R
CvWith RMSECV be 0.84447 and 0.582.Its best preprocess method of stearic NITS model is second order+Nd, R
cWith RMSEC be 0.73378 and 0.380, R
CvWith RMSECV be 0.69114 and 0.405.The best preprocess method of the NITS model of unsaturated fatty acid is a second order, R
cWith RMSEC be 0.78823 and 0.635, R
CvWith RMSECV be 0.67440 and 0.771.
4) set up each fatty acid NITS model tuning collection of tea oil and checking collection
110 kinds of samples that collect are divided into 90 modeling sample collection and 20 verification sample collection, and the maximal value of its various content of fatty acid, minimum value, average, standard deviation are listed in table 9.Can adopt the PRESS function in the time of modeling, reject the difference value, obtain the number of the near-infrared model of different chemical composition.The SD of oleic acid and linoleic calibration set is respectively 3.1351 and 2.4452, and coverage is bigger, has good representativeness, can predict unknown sample well.The SD of the calibration set of palmitic acid and unsaturated fatty acid is 1.0896 and 1.0381, predicts unknown sample preferably.Obtained the NITS model of oleic acid, linoleic acid, palmitic acid, stearic acid and unsaturated fatty acid by different preprocessing procedures, it proofreaies and correct coefficient of determination R
cBe respectively 0.93446,0.96538,0.88789,0.73378 and 0.80606, cross validation coefficient of determination R
CvBe respectively 0.91987,0.95755,0.84447,0.69114 and 0.65375.
The relative content statistics (%) of each fatty acid of table 9 tea oil
5) external certificate of each fatty acid NITS model of tea oil
The NITS model carries out accidental validation to each content of fatty acid in the unknown sample.Carry out external inspection with the near infrared light spectrum model of having set up, predicted value and GC assay value are compared, the external certificate graph of a relation of the NITS of oleic acid, linoleic acid, palmitic acid, stearic acid, unsaturated fatty acid is as 7.The NITS model that uses each fatty acid to set up detects unknown sample, obtains oleic acid and linoleic R
2Reach 0.9424 and 0.9682, the R of palmitic acid
2Be 0.8862, the R of stearic acid and unsaturated fatty acid
2Be respectively 0.6834,0.7587.It uses the ability size of NITS model express-analysis unknown sample to be linoleic acid＞oleic acid＞palmitic acid＞unsaturated fatty acid＞stearic acid.
1) preparation of binary system miscella
Tea oil and other edible vegetable oil, as soybean oil, palm oil, rapeseed oil and corn oil, preferred soybean oil, make different quality number percent (1: 0-1.5), present embodiment scope 1: 0-0.5 prepares 50-80 miscella sample, and all sample is divided into two parts, calibration set 50-60 and inspection set 10-20,15 of 51 of present embodiment selection calibration sets and inspection sets.As table 10.
Table 10 is mingled the statistics (%) of tea oil
2) foundation of miscella sample NITS model
Adopt Fourier's near-infrared transmittance, be applied to the miscella binary system sample of different proportion, with R
Cv, the RMSECV parameter determines best preprocess method and homing method, sets up the quantitative NITS model of other food plant oil content that mixes in the fast detecting tea oil, to the quantitative test at random of miscella sample.
Present embodiment is an example to mix soybean oil, by the optimization of various preprocessing procedures and homing method, has set up the optimum near infrared light spectrum model of mixing pseudo-tea oil, and the correction chart and the cross validation figure of the NITS model of building see Fig. 8.Under the selection with the homing method of the best preprocess method of " second derivative+Nd " and PLS, optimum wave band is 5037.16～4728.60cm
-1, 7852.72～7089.04cm
-1, 8577.82～8323.26cm
-1Best main cause subnumber is 6.Its R
c, RMSEC, R
Cv, RMSECV is respectively 0.99999,0.0577,0.99999,0.0719.The result is as table 11-12.
The different preprocessing procedures of table 11 is to the influence of the tea oil near-infrared model that is mixed with soya-bean oil
Annotate: SG:Savitzky-Golay filter; Nd:Norris derivative filter
The different homing method of table 12 is to the influence of the tea oil near-infrared model that is mixed with soya-bean oil
3) mix pseudo-tea oil NITS model reappearance experiment
In order to investigate the reappearance of near infrared spectroscopy, sample is carried out 4 spectral scans, the model that uses this experiment to set up predicts that 4 times predict the outcome is 36.596%, 36.559%, 36.548%, 36.568%, and actual value is 36.463%.Standard deviation is 0.021 as calculated, and RSD is 0.01%, and this method has good reappearance.
4) mix the external certificate of pseudo-tea oil NITS model
Present embodiment is an example to mingle soybean oil, constitutes tea oil binary system miscella, at random the unknown sample of 15 variable concentrations soybean oils is carried out the external inspection of model.Actual value and NITS predicted value are carried out linear regression, its R
2Up to 0.9998, has good linear relationship, as Fig. 9.Credit is analysed by statistics, and the predicted value and the actual value of NITS model carried out Paired Samples Test, and the t value is 0.659, and p=0.521＞0.05 does not have significant difference.So the external certificate method of present embodiment NITS model can apply to the content detection that soya-bean oil in the pseudo-tea oil is mixed in quantitative test well.
Claims (6)
1. a near-infrared transmission spectrum (NITS) fast detecting original flavor tea oil fatty acid and false distinguishing method, the content that it is characterized in that oleic acid, linoleic acid, palmitic acid, stearic acid and total unsaturated fatty acid in Fourier's near-infrared transmission spectral analysis technique (NITS) mensuration different cultivars tea oil, and differentiate fast and mix other edible vegetable oil in the tea oil, form by following steps:
The screening of first step high-quality oil tea kind
The screening oil content is at the fine quality of 30%-60% from more than 130 tea seed kinds, oleic acid content 65%-85% wherein, linoleic acid content 5%-20%, palmitic acid content 3%-15%, stearic acid content 1%-5%;
The foundation of second step each fatty acid NITS model of tea oil
Gather 90-140 different tea oil samples, be divided into 90-110 modeling sample collection and 20-30 verification sample collection, measure spectrum scope 4000-12000cm
-1, scanning times is 64 times, resolution is 16cm
-1, 2 multiplication benefits.Adopt the PRESS function, reject the difference value, adopt optimal spectrum preprocess method, main cause subnumber, spectral band, obtain the near-infrared model of the content of oleic acid, linoleic acid, palmitic acid, stearic acid and total unsaturated fatty acid respectively, it proofreaies and correct the coefficient of determination at 0.9999-0.7000, and the cross validation coefficient of determination is at 0.9999-0.6500;
The external certificate of the 3rd step each fatty acid NITS model of tea oil
By tea oil fatty acid NITS model unknown sample is detected, GC assay value and NITS predicted value are compared, and draw corresponding relation figure, the external certificate coefficient R
2Be respectively 0.6800-0.9950;
The preparation of the 4th step binary system miscella
In tea oil and other edible vegetable oil mass percent is 1: 0-1.5 (ratio of mingling is 0-60%), prepare 50-80 miscella sample, and all sample is divided into two parts, calibration set 50-60 and inspection set 10-20;
The foundation that the 5th step was mixed pseudo-tea oil NITS model
Adopt Fourier's near-infrared transmittance, be applied to the miscella binary system sample of different proportion, with the best preprocess method of " second derivative+Norris derivative filter " and the homing method of PLS, set up the quantitative NITS model of other food plant oil content that mixes in the fast detecting tea oil, to the quantitative test at random of miscella sample;
The evaluation that the 6th step was mixed pseudo-tea oil NITS model
NITS model by tea oil binary system miscella detects unknown sample, actual value and NITS predicted value is compared gained external certificate coefficient R
2Be respectively 0.6800-0.9999, doping tea oil is estimated.
2. according to the described a kind of near-infrared transmission spectrum of claim 1 (NITS) fast detecting original flavor tea oil fatty acid and false distinguishing method, it is characterized in that other edible vegetable oil is a kind of in palm oil, soybean oil, rapeseed oil and the corn oil;
3. according to the described a kind of near-infrared transmission spectrum of claim 1 (NITS) fast detecting original flavor tea oil fatty acid and false distinguishing method, it is characterized in that oil content is measured the cable-styled extraction method of employing in the step 1, extraction agent is sherwood oil (60 ℃-90 ℃), solid-to-liquid ratio is 1: 10-40 (g/mL), extract 70 ℃-95 ℃ of temperature, extraction time 4-10h;
4. according to the described a kind of near-infrared transmission spectrum of claim 1 (NITS) fast detecting original flavor tea oil fatty acid and false distinguishing method, the assay that it is characterized in that oleic acid in the step 1, linoleic acid, palmitic acid, stearic acid and total unsaturated fatty acid adopts GC, chromatographic column is selected SE-30 for use, flame ionization ditector (FID), 280 ℃ of injector temperatures, 280 ℃ of detector temperatures, 200 ℃ of column temperatures, continue 5min, be warming up to 270 ℃, continue 1min with the speed of 5 ℃ of per minutes;
5. according to the described a kind of near-infrared transmission spectrum of claim 1 (NITS) fast detecting original flavor tea oil fatty acid and false distinguishing method, it is characterized in that the binary system miscella is the miscella of any formation in tea oil and other edible vegetable oil (palm oil, soybean oil, rapeseed oil and corn oil) in the step 4;
6. according to the described a kind of near-infrared transmission spectrum of claim 1 (NITS) fast detecting original flavor tea oil fatty acid and false distinguishing method, it is characterized in that this method is suitable for the false distinguishing of tea oil binary system miscella, the ratio of other a kind of edible vegetable oil that mixes in the tea oil is less than 60%.
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