CN102323185B - Method for detecting honey sources - Google Patents
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- CN102323185B CN102323185B CN 201110252045 CN201110252045A CN102323185B CN 102323185 B CN102323185 B CN 102323185B CN 201110252045 CN201110252045 CN 201110252045 CN 201110252045 A CN201110252045 A CN 201110252045A CN 102323185 B CN102323185 B CN 102323185B
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Abstract
The invention discloses a method for detecting honey sources. The method comprises the following steps of: (1) measuring a honey sample into a sample groove special for a rheometer, submerging a rotor of the rheometer into honey, setting the shearing rate range of the rotor and measuring the viscosity value of the honey by using the rotor; (2) adjusting the temperature of a rheometer water bath and measuring the viscosity values of the honey at different temperatures respectively by using the rotor; (3) establishing a main component analysis and clustering analysis mode recognition model by using the viscosity values of the honey sample at different temperatures to perform qualitative analysis on the honey sources; and (4) marking an encoding value for predicting respectively for honey of different honey sources and establishing a main component regression analysis predictive model by using the viscosity values of the honey sample at different temperatures to perform predictive analysis. During the implementation of the method, preprocessing is not required, so that the experiment steps are simplified, and the reliability and repeatability are enhanced greatly.
Description
Technical field
The present invention relates to detection method, relate in particular to the detection method in a kind of honey nectar source.
Background technology
Honey is a kind of natural materials, is that honeydew and sugar part were assembled and is stored in the honeycomb during honeybee will be spent, and ferments through a series of fermentation then to form.Multiple factor can influence the quality of honey quality, and the evaluation in the honey nectariferous plant and the place of production also is a very complicated job.
Classic method is for using pollen and the raw sugar in the microexamination honey, and still this method is because need those skilled in the art, so the scope of using is little.People utilized Abbe refractometer, spectrophotometer, high performance liquid chromatograph and PH meter etc. (for example: nectar source honey such as China fir flower, Chinese photinia flower, chestnut, lavandula, robiniae,flos, rape flower and heronsbill) pH value, diastase, hydroxymethylfurfural, monose, polysaccharide and the free acid in the sample detected to the honey in different plants nectar source in the past; Use these several kinds of physical and chemical indexs, with physical and chemical index through the principal component analysis (PCA) Algorithm Analysis, the result shows that using these several kinds of physical and chemical indexs can only distinguish part nectar source honey.Also once utilize atomic absorption spectrophotometer (AAS) that the iron in the sample of zones of different honey, copper, zinc, potassium, sodium, magnesium, calcium, caesium and lithium are detected, and utilized the principal component analysis (PCA) algorithm to distinguish the honey of zones of different then.Also have ash content, total acid and viscosity number in the individual sample of different nectar sources honey (rape flower, honeydew, spend honey, acacia, Chinese photinia flower, multiflora rose, Buckwheat Flower and bodhi in vain) are detected, distinguish research after the capable discriminatory analysis of warp.In these methods, often distinguish the nectar source of honey through the physical and chemical index of using exact instrument detection honey samples such as high performance liquid chromatograph, mass spectrometer, refractometer and spectrophotometer, though viscosity number is also used, just use as auxiliary characteristics.These exact instrument price comparisons are expensive, and it is high to detect cost, in use operate more complicated and very high to technician's requirement, and The pretreatment bothers very much simultaneously, can't realize the fast detecting in honey nectar source.
Summary of the invention
The objective of the invention is to overcome the deficiency of prior art, the detection method in a kind of honey nectar source is provided.
The step of the detection method in honey nectar source is following:
1) adopt flow graph, flow graph is made up of rotor, sample cell, electrical control gear and water-bath device four parts; Electrical control gear links to each other with rotor top, and the rotor below is deep in the sample cell, and sample cell links to each other with the waters device through coil pipe; Rotor is used to detect the viscosity number of honey sample, and sample cell is used for the splendid attire honey sample, and electrical control gear is used to control the shear rate of rotor, and the water-bath device is used to control the temperature of honey sample;
2) be that the honey sample of V is poured in the sample cell of flow graph with volume, and with flow graph rotor be inserted in the honey, the honey content in the flow graph sample cell and the volume ratio of sample cell are not less than 3:5;
3) the water-bath device of adjusting flow graph, the honey sample temperature in the control sample cell progressively rises to 40 ℃ by 20 ℃, and the shear rate of setting rotor is 2-100S
-1, sampling rate be per second once, the sampling time of every kind of honey sample is 120 seconds, measures the viscosity number of honey when 20 ℃, 30 ℃ and 40 ℃ respectively; Getting shear rate is 49.7S
-1The time viscosity number be used for pattern recognition analysis as character numerical value;
4) use that the viscosity number of honey sample when 20 ℃, 30 ℃ and 40 ℃ set up principal component analysis (PCA) and the cluster analysis pattern recognition model carries out qualitative analysis to the honey nectar source;
5) honey in different nectar sources is demarcated an encoded radio that supplies prediction to use separately, and set up the honey nectar source and encoded radio concerns one to one; Encoded radio is the numeral of 0-9, and each numeral is used to represent a kind of honey;
6) being independent variable with the viscosity number of honey sample when 20 ℃, 30 ℃ and 40 ℃, is that the principal component regression forecast model that dependent variable is set up following honey nectar source carries out forecast analysis to the honey nectar source with the encoded radio in honey nectar source,
The principal component regression forecast model in honey nectar source is:
R
y?=?X
1?+?V
20X
2?+?V
30X
3?+?V
40X
4
R
yThe encoded radio in honey nectar source for prediction; V
nViscosity number for honey sample rheometer measurement when 20 ℃, 30 ℃ and 40 ℃; X
nBe honey nectar source prediction model parameters.
Described step 4) is: on principal component analysis (PCA) and cluster analysis result figure; Sample with same nature can flock together; If in principal component analysis (PCA) and cluster analysis result figure based on flow graph; The honey sample that flocks together belongs to same nectar source, and does not intersect between the honey sample in different nectar sources, explains that then flow graph can be used for distinguishing the honey in different nectar sources.
Described step 5) is: every kind of honey nectar source encoded radio mainly is to confirm through analyzing the viscosity number and the correlativity between encoded radio of this nectar source honey when 20 ℃, 30 ℃ and 40 ℃; At first the honey in different nectar sources is demarcated an original coding value separately, utilize honey regression analysis model between viscosity number binding pattern recognition methods foundation and the original coding value when 20 ℃, 30 ℃ and 40 ℃ then, carry out linear fit with the result and the original coding value of regretional analysis; Make correlation analysis; When coefficient R >=0.8, judge that then the regretional analysis result is effective, the original coding value can become corresponding relation with the honey nectar source; As coefficient R ﹤ 0.8; Judge that then the regretional analysis result is invalid, the original coding value can not become corresponding relation with the honey nectar source, just needs once more selected encoded radio; And carry out same decision process, till finding the efficient coding value.
The present invention can use the nectar source that common flow graph detects honey.Compare with traditional instrument, flow graph has reduced the detection cost, has simplified the detection step, has improved detection efficiency.The present invention uses the viscosity number of honey under different temperatures and has set up qualitative and forecast model, and these models utilize the viscosity number qualitative analysis accurately of different temperatures honey and the nectar source of prediction honey, and can obtain and the corresponding to result of conventional sense method.The rotor of flow graph can detect nectar source information different in the honey, and uses these information and set up pattern recognition model, according to the nectar source of model qualitative analysis with prediction honey.
Description of drawings
Fig. 1 (a) is the flow graph structural representation;
Fig. 1 (b) is the rotor structure synoptic diagram of flow graph;
Fig. 2 is the rheological characteristics figure of acacia honey sample in the time of 30 ℃;
Fig. 3 (a) is the result of the bidimensional principal component model of five kinds of nectar source honey of test;
Fig. 3 (b) is the result of the three-dimensional principal component model of five kinds of nectar source honey of test;
Fig. 4 is the tree-shaped result of Euclidean distance-cluster analysis of five kinds of nectar source honey of test;
Fig. 5 is based on the principal component regression predicted results of five kinds of nectar source honey of test.
Embodiment
The step of the detection method in honey nectar source is following:
1) adopt flow graph, flow graph is made up of rotor, sample cell, electrical control gear and water-bath device four parts; Electrical control gear links to each other with rotor top, and the rotor below is deep in the sample cell, and sample cell links to each other with the waters device through coil pipe; Rotor is used to detect the viscosity number of honey sample, and sample cell is used for the splendid attire honey sample, and electrical control gear is used to control the shear rate of rotor, and the water-bath device is used to control the temperature of honey sample;
2) be that the honey sample of V is poured in the sample cell of flow graph with volume, and with flow graph rotor be inserted in the honey, the honey content in the flow graph sample cell and the volume ratio of sample cell are not less than 3:5;
3) the water-bath device of adjusting flow graph, the honey sample temperature in the control sample cell progressively rises to 40 ℃ by 20 ℃, and the shear rate of setting rotor is 2-100S
-1, sampling rate be per second once, the sampling time of every kind of honey sample is 120 seconds, measures the viscosity number of honey when 20 ℃, 30 ℃ and 40 ℃ respectively; Getting shear rate is 49.7S
-1The time viscosity number be used for pattern recognition analysis as character numerical value;
4) use that the viscosity number of honey sample when 20 ℃, 30 ℃ and 40 ℃ set up principal component analysis (PCA) and the cluster analysis pattern recognition model carries out qualitative analysis to the honey nectar source;
5) honey in different nectar sources is demarcated an encoded radio that supplies prediction to use separately, and set up the honey nectar source and encoded radio concerns one to one; Encoded radio is the numeral of 0-9, and each numeral is used to represent a kind of honey;
6) being independent variable with the viscosity number of honey sample when 20 ℃, 30 ℃ and 40 ℃, is that the principal component regression forecast model that dependent variable is set up following honey nectar source carries out forecast analysis to the honey nectar source with the encoded radio in honey nectar source,
The principal component regression forecast model in honey nectar source is:
R
y?=?X
1?+?V
20X
2?+?V
30X
3?+?V
40X
4
R
yThe encoded radio in honey nectar source for prediction; V
nViscosity number for honey sample rheometer measurement when 20 ℃, 30 ℃ and 40 ℃; X
nBe honey nectar source prediction model parameters.
Described step 4) is: on principal component analysis (PCA) and cluster analysis result figure; Sample with same nature can flock together; If in principal component analysis (PCA) and cluster analysis result figure based on flow graph; The honey sample that flocks together belongs to same nectar source, and does not intersect between the honey sample in different nectar sources, explains that then flow graph can be used for distinguishing the honey in different nectar sources.
Described step 5) is: every kind of honey nectar source encoded radio mainly is to confirm through analyzing the viscosity number and the correlativity between encoded radio of this nectar source honey when 20 ℃, 30 ℃ and 40 ℃; At first the honey in different nectar sources is demarcated an original coding value separately, utilize honey regression analysis model between viscosity number binding pattern recognition methods foundation and the original coding value when 20 ℃, 30 ℃ and 40 ℃ then, carry out linear fit with the result and the original coding value of regretional analysis; Make correlation analysis; When coefficient R >=0.8, judge that then the regretional analysis result is effective, the original coding value can become corresponding relation with the honey nectar source; As coefficient R ﹤ 0.8; Judge that then the regretional analysis result is invalid, the original coding value can not become corresponding relation with the honey nectar source, just needs once more selected encoded radio; And carry out same decision process, till finding the efficient coding value.
Embodiment
The shear rate and the range of viscosities of the flow graph that the present invention adopts are respectively 0.01-4000 1/s and 1-109 mPas.This flow graph has 2 rotors: one is the spindle-type rotor, and another is the rotor that has 4 blades.This flow graph can be worked under 2 kinds of patterns: control shear rate (CSR) and control shear stress (CSS).The speed and the moment of torsion that are rotor can be regulated as required automatically, and the big I of viscosity and shear stress is calculated by the speed and the moment of torsion of flow graph through rotor automatically, and are stored in the computing machine.This instrument has constant temperature water bath apparatus (temperature-control range :-20 ℃～+ 80 ℃, error: ± 0.1 ℃), can make sample in test process, be in temperature constant state.
Sample to detecting carries out the rheometer measurement based on the spindle-type rotor.Honey sample is measured in the special-purpose sample cell of flow graph, and with flow graph rotor be inserted in the honey, set the range of shear rate of rotor then, utilize rotor to measure the honey viscosity number.The temperature of adjustment water-bath progressively rises to 40 ℃ by 20 ℃, and utilizes rotor to measure the viscosity number of honey when 20 ℃, 30 ℃ and 40 ℃ respectively, and this viscosity number is converted into digital signal by flow graph and is input to computing machine.
With computing machine the data of gained are carried out that eigenwert is extracted and pattern recognition process, adopt qualitative and forecast method respectively like principal component analysis (PCA), cluster analysis and main composition regression model.Set up the mathematical model in honey sample viscosity number and honey nectar source through these PRSs: wherein use honey sample and set up principal component analysis (PCA) and the cluster analysis pattern recognition model carries out qualitative analysis to the honey nectar source at the viscosity number of honey during 20 ℃, 30 ℃ and 40 ℃; Using the viscosity number of honey when 20 ℃, 30 ℃ and 40 ℃ sets up the principle component regression forecast model forecast analysis is carried out in the honey nectar source.
Combine instance to introduce implementation process of the present invention in detail at present.Instance is to utilize the present invention the honey in different nectar sources to be detected and predicts the nectar source of sample.Test specimen is the honey in five kinds of different nectar sources, can know that according to the mark on the trade mark sample is respectively acacia honey, clover honey, buckwheat honey, Mel Jujubae and chaste tree nectar.Testing process to honey can be following:
In the environment that honey sample storage to be detected is-18 ℃.Test the previous day, sample is taken out place room temperature (26 ± 2 ℃) a whole night (12 hours).During experiment, honey sample can directly join the scale mark in sample cell (capacity is 56ml) in the special sample cell of flow graph (Fig. 1).In this experiment, select the shear rate control model for use, the variation range of shear rate is set at 2-100S
-1Because the density of honey is not very big, selects for use the spindle-type rotor as thruster.After treating that sample cell fixes, set the flow graph program, the detection of each sample all is divided into three processes: first process is that sample stirs process, and time set was 20 seconds, and the velocity variations of rotor is 2-100S
-1Second process is that sample is stablized static process, and time set was 10 seconds, and the speed of rotor is 0; The 3rd process is the sample detection process, and time set was 120 seconds, and the velocity variations of rotor is 2-100S
-1Progressively rise to 40 ℃ through constant temperature water bath apparatus control sample temperature, and utilize rotor to measure the viscosity number of honey when 20 ℃, 30 ℃ and 40 ℃ respectively by 20 ℃.The honey in each nectar source has 8 repeat samples, totally 40 samples.After each sample is tested and finished, regulate the experimentation that temperature repeats a temperature in a temperature environment, finish up to the whole tests of 3 temperature.As shown in Figure 2, horizontal ordinate is the shear rate of rotor, and ordinate is respectively the shear stress of rotor and the viscosity number of honey.Honey through these 5 kinds of different nectar sources under different temperatures the flow graph response signal can know that these 5 kinds of honey samples belong to newton's body, its viscosity is not followed the variation of shear rate and is changed.
Detect in the experiment of 5 kinds of different nectar sources honey at flow graph, getting shear rate is 49.7S
-1The time viscosity number carry out pattern recognition analysis as eigenwert.Based on the honey in the 5 kinds of different nectar sources viscosity number when 20 ℃, 30 ℃ and 40 ℃ respectively, Using P CA carries out the nectar source compartment analysis to 5 kinds of honey in this instance.Analysis result shown in Fig. 3 (a), first principal component (PC
1) and Second principal component, (PC
2) this 2 dimension major component contribution rate addition comprised 93.08% sample primary data information (pdi) amount, except that 2 chaste tree nectar and buckwheat honey sample were interlaced, all the other samples all can be distinguished.Shown in Fig. 3 (b), first principal component (PC
1), Second principal component, (PC
2) and the 3rd major component (PC
3) this 3 dimension major component contribution rate addition comprised 100% sample primary data information (pdi) amount, because comprised more characteristic information, so all 5 kinds of samples are all by separately clear.
This exemplary application is carried out the nectar source cluster analysis based on the clustering methodology of a square conversion-Euclidean distance (minimum distance) to 5 kinds of honey, and the result is as shown in Figure 4.Wherein, when distance B=0.1328, the honey in 5 kinds of different nectar sources is divided into 2 groups: (1) acacia honey 1-8 and clover honey 1-8, (2) Mel Jujubae 1-8, chaste tree nectar 1-8 and buckwheat honey 1-8.This classifying quality is similar with Fig. 2, and in Fig. 2, the distance of honey sample is greater than the distance of sample in the group between group.In distance B=0.0739 o'clock, 5 kinds of honey samples have been divided into 5 groups: (1) clover honey 1-8, (2) acacia honey 1-8, (3) buckwheat honey 1-8, Mel Jujubae 5 and chaste tree nectar 5, (4) chaste tree nectar 1-4 and 6-8, (5) Mel Jujubae 1-4 and 6-8.In this distance, its classification and Fig. 3 are different, and wherein 2 samples are misjudged, and classification accuracy rate is 95%.
In instance, PCR is used to do the prediction in honey nectar source.The honey in 5 kinds of different nectar sources has been demarcated an encoded radio that supplies prediction to use separately: acacia honey is 2, clover honey is 1, buckwheat honey is 5, Mel Jujubae be 3 and chaste tree nectar be 4.The viscosity number when 20 ℃, 30 ℃ and 40 ℃ is as the independent variable of principal component regression model respectively for the honey of using 5 kinds of different nectar sources, and the encoded radio of nectar source honey is set up forecast model as dependent variable.Its modeling result is:
R
y?=?-6.6011+0.3105×V
20+1.1328×V
30+3.2105×V
40
R
yThe encoded radio in honey nectar source for prediction; V
nViscosity number for honey sample rheometer measurement when 20 ℃, 30 ℃ and 40 ℃; X
nBe honey nectar source prediction model parameters.
Honey nectar source encoded radio and the actual coding value of utilizing above-mentioned model prediction to obtain are made linear fit, and fitting result is as shown in Figure 5, R
2=0.8132.
Claims (3)
1. the detection method in a honey nectar source is characterized in that its step is following:
1) adopt flow graph, flow graph is made up of rotor, sample cell, electrical control gear and water-bath device four parts; Electrical control gear links to each other with rotor top, and the rotor below is deep in the sample cell, and sample cell links to each other with the water-bath device through coil pipe; Rotor is used to detect the viscosity number of honey sample, and sample cell is used for the splendid attire honey sample, and electrical control gear is used to control the shear rate of rotor, and the water-bath device is used to control the temperature of honey sample;
2) be that the honey sample of V is poured in the sample cell of flow graph with volume, and with flow graph rotor be inserted in the honey, the honey content in the flow graph sample cell and the volume ratio of sample cell are not less than 3:5;
3) the water-bath device of adjusting flow graph, the honey sample temperature in the control sample cell progressively rises to 40 ℃ by 20 ℃, and the shear rate of setting rotor is 2-100S
-1, sampling rate be per second once, the sampling time of every kind of honey sample is 120 seconds, measures the viscosity number of honey when 20 ℃, 30 ℃ and 40 ℃ respectively; Getting shear rate is 49.7S
-1The time viscosity number be used for pattern recognition analysis as character numerical value;
4) use that the viscosity number of honey sample when 20 ℃, 30 ℃ and 40 ℃ set up principal component analysis (PCA) and the cluster analysis pattern recognition model carries out qualitative analysis to the honey nectar source;
5) honey in different nectar sources is demarcated an encoded radio that supplies prediction to use separately, and set up the honey nectar source and encoded radio concerns one to one; Encoded radio is the numeral of 0-9, and each numeral is used to represent a kind of honey;
6) being independent variable with the viscosity number of honey sample when 20 ℃, 30 ℃ and 40 ℃, is that the principal component regression forecast model that dependent variable is set up following honey nectar source carries out forecast analysis to the honey nectar source with the encoded radio in honey nectar source,
The principal component regression forecast model in honey nectar source is:
R
y?=?X
1?+?V
20X
2?+?V
30X
3?+?V
40X
4
R
yThe encoded radio in honey nectar source for prediction; V
nViscosity number for honey sample rheometer measurement when 20 ℃, 30 ℃ and 40 ℃; X
nBe honey nectar source prediction model parameters, described honey nectar source is acacia honey, clover honey, buckwheat honey, Mel Jujubae and chaste tree nectar.
2. the detection method in a kind of honey according to claim 1 nectar source; It is characterized in that described step 4) is: on principal component analysis (PCA) and cluster analysis result figure; Sample with same nature can flock together, if in principal component analysis (PCA) and cluster analysis result figure based on flow graph, the honey sample that flocks together belongs to same nectar source; And do not intersect between the honey sample in different nectar sources, explain that then flow graph can be used for distinguishing the honey in different nectar sources.
3. the detection method in a kind of honey according to claim 1 nectar source is characterized in that described step 5) is: every kind of honey nectar source encoded radio mainly is to confirm through analyzing the viscosity number and the correlativity between encoded radio of this nectar source honey when 20 ℃, 30 ℃ and 40 ℃; At first the honey in different nectar sources is demarcated an original coding value separately, utilize honey regression analysis model between viscosity number binding pattern recognition methods foundation and the original coding value when 20 ℃, 30 ℃ and 40 ℃ then, carry out linear fit with the result and the original coding value of regretional analysis; Make correlation analysis; When coefficient R >=0.8, judge that then the regretional analysis result is effective, the original coding value can become corresponding relation with the honey nectar source; As coefficient R ﹤ 0.8; Judge that then the regretional analysis result is invalid, the original coding value can not become corresponding relation with the honey nectar source, just needs once more selected encoded radio; And carry out same decision process, till finding the efficient coding value.
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| CN102607924B (en) * | 2012-02-29 | 2012-11-21 | 新疆大学 | Method for identifying actual attributes of unifloal honey |
| CN103278573B (en) * | 2013-04-26 | 2014-11-26 | 中国农业科学院蜜蜂研究所 | Method for identifying rape honey and vervain family honey |
| CN109408835B (en) * | 2017-08-15 | 2023-06-09 | 廊坊立邦涂料有限公司 | Wall putty construction rheological parameter range determination method |
| CN108072742A (en) * | 2017-12-21 | 2018-05-25 | 西北大学 | A kind of method for differentiating maturated oil honey |
| DE102018129457B3 (en) * | 2018-11-22 | 2020-03-26 | Schaeffler Technologies AG & Co. KG | Procedure for determining lubricant properties |
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| CN101393122A (en) * | 2008-10-31 | 2009-03-25 | 中国农业大学 | Honey quality rapid detection method |
| CN101413885A (en) * | 2008-11-28 | 2009-04-22 | 中国农业科学院蜜蜂研究所 | Near-infrared spectrum method for rapidly quantifying honey quality |
| CN101871875A (en) * | 2010-06-02 | 2010-10-27 | 何庆生 | Honey authenticity and quality appraisal detection method |
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| CN101393122A (en) * | 2008-10-31 | 2009-03-25 | 中国农业大学 | Honey quality rapid detection method |
| CN101413885A (en) * | 2008-11-28 | 2009-04-22 | 中国农业科学院蜜蜂研究所 | Near-infrared spectrum method for rapidly quantifying honey quality |
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