CN101393122A - Honey quality rapid detection method - Google Patents
Honey quality rapid detection method Download PDFInfo
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- CN101393122A CN101393122A CN 200810225381 CN200810225381A CN101393122A CN 101393122 A CN101393122 A CN 101393122A CN 200810225381 CN200810225381 CN 200810225381 CN 200810225381 A CN200810225381 A CN 200810225381A CN 101393122 A CN101393122 A CN 101393122A
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Abstract
The invention provides a quick detection method for detecting the content of various compositions in honey by utilization of a mathematical model between a near infrared spectrum of the honey and the contents of the various compositions of the honey, in order to overcome the defects of complex operation and labor and time consumption in a chemical and chromatographic analysis method for detecting the quality of the honey. The quick detection method for the quality of the honey is as follows: firstly, obtaining a honey sample in the homogeneous fluid state; secondly, acquiring the near infrared spectrum; and thirdly, converting the near infrared spectrum acquired into the quality parameter of the honey by utilization of the mathematical model. The quick detection method for the quality of the honey can quickly and accurately detect the contents of water, soluble solid content, organic acid, fructose, glucose, sucrose and maltose in the honey.
Description
Technical field
The present invention relates to the honey quality detection method, particularly, relate to the near infrared spectrum that utilizes honey and the mathematical model between each component content of honey each component content of honey is carried out method for measuring.
Background technology
Honey is meant that the nectar of honeybee herborization or the particular matter of secretion through self containing fully brewage the sweet substance that forms.Honey is natural health food, is again natural medicine.
The development of honey quality detection technique is the important sharp weapon that guarantee product quality, hit counterfeit and shoddy goods.Traditional chemistry and stratographic analysis analytical approach complicated operation, time-consuming, effort.
Near-infrared spectrum technique is with fastest developing speed, one of the most noticeable spectral analysis technique.So-called near infrared light is meant wavelength in the 780-2526nm scope, a kind of electromagnetic wave between visible light and infrared light.Near infrared spectrum reflects that mainly the frequency multiplication and the sum of fundamental frequencies of hydrogeneous radicals X-H vibration absorb information.Be used at present the detection of oil, the medium organic principle of tobacco.Principal ingredient in the honey such as moisture, glucose, fructose, soluble solid etc. all contain hydroxyl or carbonyl, and therefore, theoretically, near-infrared spectral analysis technology also can be used for the chemical composition content analysis of honey.Just because complicated component, the state thickness of honey also do not have near-infrared spectral analysis technology to be effectively applied at present the chemical composition content analysis of honey.
Summary of the invention
In order to solve chemistry and the chromatogram analysis method complicated operation that honey quality detects, time-consuming, as to require great effort shortcoming the invention provides a kind of near infrared spectrum of honey and method for quick that the mathematical model between each component content of honey is measured each component content of honey of utilizing.
Honey quality rapid detection method provided by the invention is: the honey to be measured that obtains even matter fluid state earlier, gather near infrared spectrum, utilize mathematical model the near infrared spectrum that collects to be converted to the Q factor of honey then, described Q factor is to be selected from the content of water, soluble solid, fructose, glucose, sucrose and maltose one or more, described mathematical model adopts partial least square method to set up, and pattern function is: y
i=x (U
iX) ' B
iQ
i, y wherein
iBe certain Q factor in the described Q factor, vector x is the near infrared spectrum of honey to be measured, U
iBe described certain Q factor concentration feature factor matrix, X is the near infrared light spectrum matrix of the modeling sample chosen, B
iBe described certain Q factor absorbance characterization factor matrix, Q
iBe concentration loading matrix, wherein U
i, B
i, Q
iDetermine by chemometrics method according to the near infrared light spectrum matrix of described modeling sample and the value of corresponding Q factor, calculate y
iAdopt classical partial least square method software.
Honey is thickness relatively, and have a crystallization, in order to make it be in even preferably matter fluid state, be convenient to gather spectrum, when detecting finished product honey, often need do water-bath heating, generally adopt 40-60 ℃ of water-bath heating more than 30 minutes, gather its spectrum again after being cooled to room temperature at the poor honey product of flowability.Not the crystallization more at once under (3 days) normal temperature in a short time of honey after the water-bath.For the detection in the production run, melt honey, concentrate etc. and to be subjected to thermal process because the production technology of honey comprises, before canned, all can directly gather its spectrum.
Described near infrared spectrum can be the near infrared spectrum in the 780-2500nm wavelength coverage.Use near infrared spectrometer, the near infrared spectrum of collected specimens in the 780-2500nm wavelength coverage.According to the difference of used spectrometer type, select different acquisition conditions for use.As for shortwave near infrared spectrometer (780-1100nm), available transmission mode, light path can be 0-50mm; For middle long wavelength near infrared spectrometry instrument (1100-2500nm), available mirror based fiber optica annex is gathered its saturating reflectance spectrum, with short light path (0-10mm).After having gathered the spectrum of a sample, need with hot water (temperature is greater than 70 ℃) flushing optical fiber head or sample cell, again with measuring next sample after the normal-temperature distilled washing only.The fibre-optical probe that is adopted needs insensitive to heat, keeps advantages of higher stability in the transfer process of being heated, cooling off.In addition, because honey compares thickness, the surface of fibre-optical probe or sample cell needs very smooth, is beneficial to clean.
Preferably, the described near infrared spectrum that collects has carried out pre-service to spectrum, described pre-service is one or more of background removal, correction, denoising and characteristic point selection, and the method for employing is that centralization, canonical variable conversion, additional scatter correction, orthogonal signal are proofreaied and correct, in level and smooth, small echo denoising, differentiate conversion and the genetic algorithm Wavelength optimization one or more.
Described mathematical model has been set up the funtcional relationship between near infrared spectrum and each component content measured value of honey, thereby can utilize the near infrared spectrum of collection to be converted to corresponding component content in the honey.During modeling, in each component content measured value of used honey, measure water cut, soluble solid content (SSC) and acidity in the honey according to the standard SN/T0852-2000 of the Ministry of Commerce (importing and exporting honey check way), according to GB GB/T 18932.22-2003 (assay method of fructose, glucose, sucrose, maltose content in the honey-liquid chromatography differential refraction detection method), measure the content of fructose, glucose, sucrose, maltose in the honey.
Described mathematical model is to adopt the near infrared spectrum of chemometrics method foundation and the quantitative model between each composition parameter of honey.The chemometrics method that adopts can comprise multiple linear regression, partial least squares regression, artificial neural network, support vector machine.Preferably, common similar honey sample was verified during described mathematical model utilization was produced, and according to the error requirements in the actual production, obtained after optimizing repeatedly.
Honey quality rapid detection method provided by the invention can detect the content of water, soluble solid, organic acid, fructose, glucose, sucrose and maltose in the honey rapidly and accurately.More particularly, somewhat following:
1. sample pre-treatments is simple.For honey processing factory, can be before canned directly measure the near-infrared transmission spectrum of honey sample, for the finished product honey on the market, can directly the measuring of good fluidity, mobile relatively poor or crystallization is through measuring after the water-bath heating.
2. quick nondestructive.The acquisition time of near infrared spectrum is very short, and the time of Model Calculation can be ignored substantially.
3. multicomponent is measured simultaneously.Can measure water cut, soluble solid content and the organic acid of honey sample simultaneously, reach the content of main sugar such as fructose, glucose, sucrose, maltose.
4. the present invention provides technical foundation for the online in real time detection of honey component.
Description of drawings
Fig. 1 is the near infrared predicted value of moisture, soluble solid, fructose content, glucose content in each honey sample and the scatter diagram between the actual value.
Embodiment
Honey quality rapid detection method provided by the invention is: the honey to be measured that obtains even matter fluid state earlier, gather near infrared spectrum, utilize mathematical model the near infrared spectrum that collects to be converted to the Q factor of honey to be measured then, described Q factor is for being selected from water, soluble solid, fructose, glucose, in the content of sucrose and maltose one or more, described mathematical model adopts partial least square method to set up, the described modeling sample of using can be selected according to the requirement of measuring accuracy,, be modeling sample just for example with North China's robiniae,flos honey in order to measure the quality of North China's robiniae,flos honey more accurately; The model of setting up in order to make is applicable to be distinguished a greater variety of honey more and allows certain measuring errors, and just the honey with how regional multiple class is modeling sample.
Modeling method with fructose content is that the present invention is described further for example below.
Modeling sample: the honey sample of having gathered each famous places of production of honey, the whole nation such as Sichuan, Qinghai-Tibet, Jiangsu, Shanxi, Shandong, Ningxia, Zhejiang, Fujian, Yunnan, Guizhou, Henan, Jilin, Jiangxi, Hunan, Hubei, Hebei, Anhui, Gansu, Xinjiang, Hebei, Beijing, not only fully represent the characteristic in the domestic sample kind and the place of production, also represented the sample of the main exit kind of China's honey.The honey kind is also representative, collect acacia, Chinese lute, jujube flower, the fruit of Chinese magnoliavine, dandelion, motherwort, the coptis, Chinese milk vetch, the twigs of the chaste tree, Radix Codonopsis, snow fat lotus, lichee, lime tree, Orchid, matrimony vine, chrysanthemum, sweet osmanthus, rose, olive, camellia, rape, oranges and tangerines, white tattooing, bluish dogbane, 25 kinds of single plant source honey of the red sage root altogether, and mixed plant source honey totally 153 samples.
Fructose content is measured: according to GB GB/T 18932.22-2003 (assay method of fructose, glucose, sucrose, maltose content in the honey-liquid chromatography differential refraction detection method).
Near infrared spectra collection: adopt ISF/28N type Fourier blade profile near infrared spectrometer to measure the saturating reflectance spectrum of honey.Gathering annex is 2mm light transmissive liquid fibre, and the scanning spectrum district is 3600-12500cm-1, and resolution is 8cm-1, and scanning times is to be averaged for 32 times.For the sample of partially crystallizable sample and comparison thickness, adopt 50 ℃ of water-baths heating 30 minutes, gather its spectrum again after being cooled to room temperature.
Spectrum pre-service: the near infrared spectrum of gathering is made centralization handle.For the near infrared light spectrum matrix X of modeling sample, every row is represented a sample, and every row are represented the absorbance of a wavelength points.Described centralization is handled, and is exactly the average that each element deducts these row in the matrix.
Modeling: adopt partial least square method to set up calibration model.Detailed process is as follows: with the fructose concentration y of spectrum matrix X after the centralization and modeling sample as the input data, be input in the partial least square method software, through interative computation, software calculates the series of parameters of partial least square model automatically, comprises fructose parameter concentration feature factor matrix U
i, fructose absorbance characterization factor matrix B
i, concentration loading matrix Q
iThereby obtain the function expression of fructose forecast model: y
i=x (U
iX) ' B
iQ
i, wherein, vector x is the near infrared spectrum of honey to be measured.
It is as follows to utilize above-mentioned model to carry out the method for honey quality fast detecting to be measured:
Gather the near infrared spectrum of honey to be measured respectively according to the method for above-mentioned near infrared spectra collection, and, utilize above-mentioned mathematical model y through obtaining the near infrared spectrum vector of honey sample to be measured after the above-mentioned spectrum pre-service
i=x (U
iX) ' B
iQ
iCan calculate the fructose content of above-mentioned honey to be measured.This computation process also can be compiled into program, imports the near infrared spectrum vector x of honey to be measured, just can calculate its fructose content automatically.
Equally, utilize said method, can set up the funtcional relationship of moisture, soluble solid content, glucose content and cane sugar content and near infrared spectrum value, thereby obtain above-mentioned various content by the near infrared spectrum value.Operating process is as follows:
The practical measurement of moisture, soluble solid content, glucose content: measure water cut, soluble solid content in the honey according to the standard SN/T 0852-2000 of the Ministry of Commerce (importing and exporting honey check way).According to GB GB/T 18932.22-2003 (assay method of glucose, sucrose, maltose content in the honey-liquid chromatography differential refraction detection method), measure the content of glucose in the honey.
Utilize above-mentioned near infrared spectra collection method to gather the infrared spectrum that advances of every kind of sample, and carry out centralization and handle.
Set up the mathematical model of each quality of honey: the picked at random sample is used for modeling, comes verification model with other sample of residue.
The result of each index partial least squares regression modeling of honey is as shown in the table.Wherein, calibration set is used for setting up model, and forecast set is used for model is verified.#LV is the number of principal components of each model in the following table; R is the related coefficient of model, and r is more near 1, and model accuracy is high more; SEC is the calibration set sample standard deviation, RSD
cAnd RPD
pBe respectively the prediction relative error of calibration set and forecast set sample.RSD
cAnd RSD
pVery accurate in explanation prediction below 5%, 10% can accept with next.RPD
cAnd RPD
pBe respectively the ratio of the standard deviation average of calibration set and forecast set, generally can do accurate prediction greater than 2.
Table 1
The result shows that the model of being set up can be predicted moisture and soluble solid very exactly, and the prediction relative standard deviation is respectively 2.34%, 0.52%.Prediction accuracy to fructose, glucose content is also higher, is respectively 5.45%, 8.81%.Illustrate that near infrared spectrum can measure the content of honey principal ingredient rapidly and accurately.
Fig. 1 is the near infrared predicted value of moisture, soluble solid, fructose content, glucose content in each honey sample and the scatter diagram between the actual value.Can find out very intuitively that method provided by the invention can measure the content of honey principal ingredient exactly.
Claims (7)
1, honey quality rapid detection method, it is characterized in that, obtain the honey to be measured of even matter fluid state earlier, gather near infrared spectrum, utilize mathematical model the near infrared spectrum that collects to be converted to the Q factor of honey to be measured then, described Q factor is to be selected from the content of water, soluble solid, fructose, glucose, sucrose and maltose one or more, and described mathematical model adopts partial least square method to set up, and pattern function is: y
i=x (U
iX) ' B
iQ
i, y wherein
iBe certain Q factor in the described Q factor, vector x is the near infrared spectrum of honey to be measured, U
iBe described certain Q factor concentration feature factor matrix, X is the near infrared light spectrum matrix of the modeling sample chosen, B
iBe described certain Q factor absorbance characterization factor matrix, Q
iBe concentration loading matrix, wherein U
i, B
i, Q
iDetermine by chemometrics method according to the near infrared light spectrum matrix of described modeling sample and the value of corresponding Q factor, calculate y
iAdopt classical partial least square method software.
2, method according to claim 1 is characterized in that, the method that obtains the honey sample of even matter fluid state is: adopt 40-60 ℃ of water-bath heating more than 30 minutes, be cooled to room temperature then.
3, method according to claim 1 is characterized in that, described near infrared spectrum is the near infrared spectrum in the 780-2500nm wavelength coverage.
4, method according to claim 1 is characterized in that, described near infrared spectrum is the near infrared spectrum in the 780-1100nm wavelength coverage, gathers near infrared spectrum with transmission mode, and light path is 0-50mm.
5, method according to claim 1 is characterized in that, described near infrared spectrum is the near infrared spectrum in the 1100-2500nm wavelength coverage, gathers near infrared spectrum with saturating mirror based fiber optica annex, and light path is 0-10mm.
6, method according to claim 1, it is characterized in that, the described near infrared spectrum that collects has carried out pre-service to spectrum, described pre-service is one or more of background removal, correction, denoising and characteristic point selection, and the method for employing is that centralization, canonical variable conversion, additional scatter correction, orthogonal signal are proofreaied and correct, in level and smooth, small echo denoising, differentiate conversion and the genetic algorithm Wavelength optimization one or more.
7, method according to claim 1 is characterized in that, described chemometrics method comprises and is selected from multiple linear regression, partial least squares regression, artificial neural network and the support vector machine one or more.
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| CN101393122B CN101393122B (en) | 2011-02-16 |
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