CN104297201A - Method for quickly, accurately and quantitatively detecting ratio of various oil components in blend oil - Google Patents
Method for quickly, accurately and quantitatively detecting ratio of various oil components in blend oil Download PDFInfo
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- CN104297201A CN104297201A CN201410616248.0A CN201410616248A CN104297201A CN 104297201 A CN104297201 A CN 104297201A CN 201410616248 A CN201410616248 A CN 201410616248A CN 104297201 A CN104297201 A CN 104297201A
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Abstract
The invention relates to a method for quickly, accurately and quantitatively detecting the ratio of various oil components in blend oil. The method comprises the following concrete steps: by taking edible oil as a research object, preliminarily analyzing and researching the content of the components in the blend oil by a near-infrared spectrometry and chemical metering combined process to expectantly find a method for quickly distinguishing the components of the blend oil so as to judge whether a type of blend oil is consistent with a label or not and judge whether the blend oil goes bad or not; experimenting and collecting multiple types of blend oil, simulating configuration of blend oil with different ratios, scanning the spectrum of pure oil and the spectrum of the blend oil through a near-infrared spectrometer, and creating a model for quantitatively analyzing the content of soybean oil, peanut oil and sunflower seed oil in the blend oil through a partial least squares (PLS) method; finally, creating a PLS prediction model by selecting and using an S-G smooth preprocessing method and proper component number, wherein due to the model, the related coefficients of the soybean oil, the peanut oil and the sunflower oil can maximally reach 0.9874, 0.9371 and 0.9456 respectively and the content of the soybean oil, the peanut oil and the sunflower oil in the blend oil can be accurately predicted. Therefore, the quality of the edible plant oil can be quickly and quantitatively analyzed by the near-infrared spectrometry and chemical metering combined process.
Description
Technical field
The invention belongs to analytical chemistry field, relate to the test problems of food plant oil quality.
Background technology
Edible oil is one of important necessity in people's daily life, and along with growth in the living standard and the pay attention to day by day to health, balanced in nutrition and cheap blending stock is more and more subject to the favor of consumer.Blending stock is admixed by two or more vegetable oil and is formed.Mainly contain in blending stock: olive oil, sesame oil, peanut oil, siritch, sunflower oil, soybean oil, corn oil, rapeseed oil, palm wet goods.But its concrete composition and price all neither one specific standards, be difficult to again judge to its content, the method having an effective judgement is difficult to for blending stock, traditional method of inspection is also difficult to make one to blending stock and judges quickly and accurately, is difficult to especially analyze especially to the proportion of wherein a certain oil.And then cause market confusion, arbitrarily give blending stock using names, but may not be certain the oil content containing using names, or containing quantity not sufficient, misguide the consumer.Research and analyse so we need to do one to mediation oil component composition, find a kind of content of effective method energy quantitative test blending stock component.
Main common methods at present for blending stock content analysis has vapor-phase chromatography, high performance liquid chromatography, thin-layered chromatography, ultraviolet spectrophotometry, infra-red sepectrometry, near infrared spectroscopy, gas chromatography mass spectrometry, nuclear magnetic resonance etc.Above method also can obtain good result, but some restrictions of existence all more or less.Chromatography of gases and liquid chromatography need to carry out a large amount of pre-service, and experimental period is longer, and the component of grease class is a lot, and data numerous and diverse being difficult to is distinguished; The discrimination of ultraviolet spectrum is not too high, and the component producing characteristic peak can be added.Be compared to infra-red sepectrometry near infrared spectrum rule more simple, near infrared spectrum is as technology out newly developed in this year, and the spectrogram that it obtains is simpler, and operation is simpler, can directly measure, and can be implemented in line and detects.The method of application near infrared spectroscopy and Chemical Measurement, a preliminary analysis and research are done for blending stock component content, to finding a method distinguishing blending stock composition fast, judge that whether a certain blending stock is consistent with label, and judge its quality.
Chemical Measurement is the cross discipline of the subjects such as chemistry, statistics, mathematics, a computer science.Chemical Measurement not only can carry out qualitative analysis but also can carry out quantitative test, and the method related to also is not quite similar.Main method comprises principal component analysis (PCA), cluster analysis, offset minimum binary-discriminatory analysis, SIMCA, support vector machine and artificial neural network etc.
In sum, developing blending stock detection method is fast and accurately improve the effective way of food security.And the present invention is using near infrared spectrum as detection means, in conjunction with stoechiometric process, the ratio realizing various oil in blending stock is quantitative.
Summary of the invention
The object of the invention is for above-mentioned Problems existing, provide a kind of fast, the detection method of various oil content ratio in accurate quantitative analysis blending stock, to being in harmonious proportion, the improvement of oil quality is significant.
Comprise the following steps for realizing technical scheme provided by the present invention:
1) collect representational sample and measure the near infrared spectrum of sample by near infrared spectroscopy instrument, adopting standard method to measure the component or character be concerned about.
2) by composition or the near infrared spectrum of character data and sample by setting up calibration model.First different preprocess methods is investigated on the impact predicted the outcome, secondly by cross validation root mean square (RMSECV) along with the change because of subnumber (LV) determine 3 kinds of components because of subnumber, finally partial least squares regression (PLS) model is set up to often kind of component.
3) according to the component of positive model for school building prediction unknown sample or character.
Its analytic process mainly comprises the near infrared spectrum of collected specimens, measures the component be concerned about or character data, sets up calibration model and the mensuration to unknown sample component or character.
The present invention adopts near infrared spectrometer as sample detection means, and near-infrared spectral measurement mode has transmission, reflection and diffuse reflection various ways, is applicable to the sample measuring the forms such as liquid, solid and pulpous state, therefore, has many uses.Maximum advantage need not carry out any pre-service to sample exactly, and directly can to pour in cuvette as vegetable oil or directly be inserted in vegetable oil by fibre-optical probe and measure, operation is very easy, completes spectral scan in a few second.
Accompanying drawing explanation
The near infrared light spectrogram of Fig. 1: 120 samples
Fig. 2: cross validation root mean square (RMSECV), along with the variation diagram because of subnumber (LV), wherein a), b), c) distinguishes corresponding peanut oil, sunflower oil and soybean oil
Fig. 3: the correlogram of forecast set sample components concentration reference value and PLS predicted value, wherein a), b), c) distinguishes corresponding peanut oil, sunflower oil and soybean oil
Embodiment
For better understanding the present invention, below in conjunction with embodiment the present invention done and describe in detail further, but the scope of protection of present invention being not limited to the scope that embodiment represents.
Embodiment:
1) blending stock near infrared spectrum is collected.Select sunflower oil, soybean oil, based on peanut oil, oily analog ligand compares blending stock.The size in pond per sample, selects 10g as gross weight.With analytical balance, add three kinds of oil in proportion.Wish configuration peanut oil content range is 1%-40% in theory, and soybean oil and sunflower oil then do not repeat to add at random.Running control software, sets measurement parameter and blank background, timebase.Nir instrument will be put into and gather spectrum, each Sample Scan three times.Spectroscopic data is preserved with txt form.Wavelength coverage 800-2500nm adopts transmission mode, transmitance, and wavelength coverage selects the interval of 1nm, faster measuring speed (1.0nm), and spectral width is selected normally, and scan mode selects multiple scanning.Fig. 1 is the near infrared light spectrogram of 120 samples.As can be seen from the figure, between each sample, gap is minimum, substantially overlaps, and directly cannot obtain content information according to peak heights, need to carry out quantitative test by Chemical Measurement.
2) six kinds of preprocess methods such as S-G is level and smooth, standard normal variable (SNV), multiplicative scatter correction (MSC), first order derivative, second derivative, continuous wavelet transform (CWT) are adopted to carry out pre-service to spectrum.The level and smooth pretreating effect of cross validation root-mean-square error display S-G is best.Setting up between PLS model, needing certainty factor number, Fig. 2 be cross validation root mean square (RMSECV) along with the variation diagram because of subnumber (LV), wherein a), b), c) respectively corresponding peanut oil, sunflower oil and soybean oil.As can be seen from the figure, RMSECV declines gradually along with the increase because of subnumber, get minimum RMSECV corresponding because of subnumber be this component because of subnumber, three kinds of component factors numbers are defined as 17,19,20 respectively.
3) spectrum of forecast set is substituted into the PLS model optimized, the ratio of various oil in prediction blending stock.Fig. 3 a), b), c) is respectively the correlogram of soybean oil in blending stock, peanut oil, sunflower oil three kinds of component actual values and predicted value.As can be seen from the figure, better, related coefficient (R) reaches 0.9874,0.9371 and 0.9456 respectively for the actual value of three kinds of components and predicted value linear relationship.
Claims (3)
1. one kind fast, the detection method of various oil content ratio in accurate quantitative analysis blending stock, it is characterized in that: it utilizes near infrared spectrometer to scan the spectrum of blending stock, adopt the method for not averaging directly to set up PLS model, establish forecast model in conjunction with optimum factor number and carry out various oil content in quantitative test blending stock.
2. each oil content detection method fast and accurately in blending stock according to claim 1, it is characterized in that: described chemometrics method first adopts SG smoothly to carry out pre-service to spectrum, after certainty factor number, partial least-square regression method is adopted to set up calibration model.
3. each oil content detection method fast and accurately in blending stock according to claim 1, is characterized in that: the proportioning for oil content each in blending stock does not limit, and can accurately detect especially to wherein right a certain oil simultaneously.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105548027A (en) * | 2015-12-09 | 2016-05-04 | 湖南省农产品加工研究所 | Analytical model and method for determining content of tea oil in blend oil based on near infrared spectroscopy |
| CN106483095A (en) * | 2016-10-13 | 2017-03-08 | 天津工业大学 | A kind of method of each component oil content in quick, accurate quantitative analysis quaternary ready-mixed oil |
| CN106525760A (en) * | 2016-10-27 | 2017-03-22 | 天津工业大学 | Method for quantitative analysis of six-ingredient blend oil |
| CN107036999A (en) * | 2016-11-15 | 2017-08-11 | 天津工业大学 | A kind of five yuan of ready-mixed oil quantitative analysis methods based near infrared spectrum and Chemical Measurement |
| CN107727591A (en) * | 2017-09-27 | 2018-02-23 | 天津工业大学 | A kind of ternary based on integrating sphere diffusing reflection uv-vis spectra mixes pseudo- pseudo-ginseng quantitative analysis method |
| CN110987862A (en) * | 2019-11-06 | 2020-04-10 | 汉谷云智(武汉)科技有限公司 | Diesel oil on-line blending method |
-
2014
- 2014-11-03 CN CN201410616248.0A patent/CN104297201A/en active Pending
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105548027A (en) * | 2015-12-09 | 2016-05-04 | 湖南省农产品加工研究所 | Analytical model and method for determining content of tea oil in blend oil based on near infrared spectroscopy |
| CN106483095A (en) * | 2016-10-13 | 2017-03-08 | 天津工业大学 | A kind of method of each component oil content in quick, accurate quantitative analysis quaternary ready-mixed oil |
| CN106525760A (en) * | 2016-10-27 | 2017-03-22 | 天津工业大学 | Method for quantitative analysis of six-ingredient blend oil |
| CN107036999A (en) * | 2016-11-15 | 2017-08-11 | 天津工业大学 | A kind of five yuan of ready-mixed oil quantitative analysis methods based near infrared spectrum and Chemical Measurement |
| CN107727591A (en) * | 2017-09-27 | 2018-02-23 | 天津工业大学 | A kind of ternary based on integrating sphere diffusing reflection uv-vis spectra mixes pseudo- pseudo-ginseng quantitative analysis method |
| CN110987862A (en) * | 2019-11-06 | 2020-04-10 | 汉谷云智(武汉)科技有限公司 | Diesel oil on-line blending method |
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