CN103592258A - Detection method of tea polyphenol contents in tea - Google Patents
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Abstract
The invention discloses a detection method of tea polyphenol contents in tea, and the detection method comprises the following steps: (1) collecting single band spectra images of to-be-detected tea leaves in fourteen characteristic wavelengths, and the fourteen characteristic wavelengths being 884nm, 905nm, 915nm, 945nm, 1019nm, 1066nm, 1382nm, 1649nm, 1676nm, 1683nm, 1697nm, 1700nm, 1717nm and 1720nm; (2) on the basis of the linear relations of the gray value and the reflectivity of the single band spectra images, converting the single band spectra images of the step (1) into reflectivity images; (3) according to a formula, calculating to obtain the tea polyphenol content of each pixel point in the reflectivity images of the tea leaves. The detection method can rapidly detect the tea polyphenol contents of the tea in random space distribution to obtain the spatial distribution information of the tea polyphenol contents in the tea.
Description
Technical field
The present invention relates to Tea Processing detection field, be specifically related to a kind of detection method of Tea Polyphenols in Tea content.
Background technology
In Tea Processing process, polyphenol content is the key factor that affects Tea Processing quality, and on detection streamline real-time, the polyphenol content of tealeaves and distribution thereof are the keys that improves Tea Processing quality.
The National Standard Method that tealeaves polyphenol content detects need to be used number of chemical reagent, extracts, is oxidized, demarcates, and operating process is more than at least 1 hour, and institute's test sample is originally grated completely and loses edibility.
Increasingly mature along with spectral technique, utilize spectrum to carry out the method for composition detection more and more general, in prior art, occurred for utilizing spectrum to carry out the method for Tea Polyphenols in Tea detection, for example, publication number be CN101059426A disclosure of the invention a kind of method based on polyphenol content in near-infrared spectrum technique non-destructive measurement for tea, model calibration model, collect tealeaves sample as calibration samples collection, and scan visible ray and the near infrared spectrum (325-2500NM) that obtains calibration samples collection, the spectroscopic data obtaining is carried out to spectrum pre-service; Then adopt the polyphenol content of the method measurement update sample of GB regulation; Adopt Multivariate Correction regression algorithm to set up the near infrared spectrum of calibration samples and the quantitative relationship between polyphenol content, set up calibration model.For tealeaves to be detected, scan their near infrared light spectrogram, and being input to calibration model through the pretreated spectroscopic data of corresponding spectrum, through the mensuration of calibration model, obtained the polyphenol content of this tealeaves.
The method is utilized collection, storage, demonstration and the processing capacity of computer realization data, polyphenol content that can fast detecting tealeaves blade, but for the distribution of polyphenol content, to have no idea to detect, the polyphenol content information of acquisition is limited.
Summary of the invention
The invention provides a kind of detection method of Tea Polyphenols in Tea content, can to the polyphenol content of any distribution tealeaves on space, carry out fast detecting simultaneously, obtain the space distribution information of tealeaves polyphenol content.
A detection method for Tea Polyphenols in Tea content, comprises the following steps:
(1) gather tealeaves blade to be measured at the single band spectrum picture of 14 characteristic wave strong points; Described 14 characteristic wavelengths are respectively 884nm, 905nm, 915nm, 945nm, 1019nm, 1066nm, 1382nm, 1649nm, 1676nm, 1683nm, 1697nm, 1700nm, 1717nm, 1720nm;
(2) according to the linear relationship of gray-scale value and the reflectivity of single band spectrum picture, the single band spectrum picture in step (1) is converted into albedo image;
(3) according to following formula, calculate the polyphenol content of each pixel in the albedo image of tealeaves blade;
Y
polyphenol content=4.004+0.01549 λ
884-0.04241 λ
905-0.002961 λ
915+ 0.02177 λ
945+ 0.05390 λ
1019-0.04165 λ
1066+ 0.02199 λ
1382-0.04560 λ
1649-0.07836 λ
1676+ 0.09637 λ
1683-0.02560 λ
1697+ 0.02705 λ
1700+ 0.01990 λ
1717-0.02124 λ
1720
In formula: λ
arepresent in the albedo image of a nm characteristic wave strong point the reflectivity of a certain pixel;
Y
polyphenol contentrepresent the polyphenol content at respective pixel point place.
As preferably, in described step (2), the obtaining step of the gray-scale value of single band spectrum picture and the linear relationship of reflectivity is as follows:
2-1, gather at least three diffuse reflection on-gauge plates at the benchmark single band spectrum picture of 14 characteristic wave strong points, ask for the gray-scale value of every width benchmark single band image, within the scope of visible and near infrared spectrum, the diffuse reflection on-gauge plate adopting has constant separately reflectivity; Different diffuse reflection on-gauge plates have different reflectivity;
2-2, for each characteristic wavelength, the gray-scale value of corresponding benchmark single band image and reflectivity are carried out to linear fit, obtain the linear relationship of gray-scale value and reflectivity.
As preferably, described diffuse reflection on-gauge plate is three～six.
In each characteristic wave strong point, every diffuse reflection on-gauge plate is a corresponding width single band image separately, the corresponding gray-scale value of every width single band image, and the gray-scale value of diffuse reflection on-gauge plate of take is independent variable, take reflectivity as dependent variable, and linear fit obtains the relation of gray-scale value and reflectivity.
The number of diffuse reflection on-gauge plate is more, the gray-scale value that linear fit obtains and the relation of reflectivity are more accurate, corresponding consuming time also longer, preferably, described diffuse reflection on-gauge plate is three, is respectively 99% diffuse reflection on-gauge plate, 75% diffuse reflection on-gauge plate and 2% diffuse reflection on-gauge plate.
99% diffuse reflection on-gauge plate refers to: within the scope of whole visible and near infrared spectrum, the reflectivity of diffuse reflection on-gauge plate is 99%.
75% diffuse reflection on-gauge plate refers to: within the scope of whole visible and near infrared spectrum, the reflectivity of diffuse reflection on-gauge plate is 75%.
2% diffuse reflection on-gauge plate refers to: within the scope of whole visible and near infrared spectrum, the reflectivity of diffuse reflection on-gauge plate is 2%.
Adopt 99% diffuse reflection on-gauge plate, 75% diffuse reflection on-gauge plate and 2% diffuse reflection on-gauge plate, at utmost contained the scope of reflectivity, make the linear relationship of the gray-scale value that obtains and reflectivity more accurate.
Adopt different diffuse reflection on-gauge plates to obtain the gray-scale value at different characteristic wavelength place and the linear relationship of reflectivity is respectively:
Y
884＝-140.0781+2.1850x
884
Y
905＝-98.3355+1.5140x
905
Y
915＝-84.9478+1.2915x
915
Y
945＝-13.4568+0.1958x
945
Y
1019＝-6.7178+0.0918x
1019
Y
1066＝-5.1557+0.0682x
1066
Y
1382＝-4.8008+0.0464x
1382
Y
1649＝-7.5836+0.0804x
1649
Y
1676＝-28.5770+0.3714x
1676
Y
1683＝-38.2493+0.5030x
1683
Y
1697＝-64.4862+0.8836x
1697
Y
1700＝-74.9443+1.0215x
1700
Y
1717＝-150.5751+2.0665x
1717
Y
1720＝-165.0176+2.2890x
1720
In formula: x
bgray-scale value for b nm characteristic wave strong point;
Y
breflectivity for b nm characteristic wave strong point.
Compared with prior art, the present invention has following useful technique effect:
(1) simple, the inventive method by obtain tealeaves the spectrum picture at 14 wave band places realize tealeaves Tea Polyphenols quantitatively and positioning analysis, this detection is without directly contacting with sample, is nondestructive measurement completely, and operating process and computing method simple.
(2) quick, the spectrum picture of the method that the present invention proposes based on 14 wave band places, image acquisition process is quick, and the spectrum picture acquisition time of a sample is less than 10 seconds, than 1 hour detection time of conventional tea polyphenol detection method, detection speed is accelerated greatly.
(3) efficient, the method that the present invention proposes can realize simultaneously tealeaves Tea Polyphenols quantitatively and detection and localization, be particularly useful in tealeaves on-line machining process, in the time of the different tealeaves polyphenol content of space distribution, detect.
Accompanying drawing explanation
Fig. 1 is the single band spectrum picture of the tealeaves at the different characteristic wavelength place measured in embodiment 1 in the present invention;
Fig. 2 is the reflectivity of three diffuse reflection on-gauge plates and the graph of a relation of wavelength;
Fig. 3 is that three diffuse reflection on-gauge plates are at the single band spectrum picture at different characteristic wavelength place;
Fig. 4 is that three diffuse reflection on-gauge plates are at the gray-scale value at different characteristic wavelength place;
Fig. 5 is the reflectivity at wavelength 1019nm place and the linear relationship of gray-scale value;
Fig. 6 is the reflectivity at wavelength 1700nm place and the linear relationship of gray-scale value;
Fig. 7 is the reflectivity of a pixel and the relation of wavelength and process of establishing schematic diagram in the single band spectrum picture of tealeaves blade;
Fig. 8 is the distribution plan of the polyphenol content of tealeaves blade;
Fig. 9 is the prediction polyphenol content of 120 tealeaves blades and the graph of a relation of true polyphenol content of measuring in embodiment 1;
Figure 10 is the prediction polyphenol content of 120 tealeaves blades and the graph of a relation of true polyphenol content of measuring in comparative example 1;
Figure 11 is the prediction polyphenol content of 120 tealeaves blades and the graph of a relation of true polyphenol content of measuring in comparative example 2.
Embodiment
Embodiment 1
First collect 120 tealeaves blades, the kind of tealeaves blade comprises 14 kind tealeaves such as purple bamboo shoot, Yun Qi, flat cloud, first adopt high spectrum image imaging system (ImSpector V10E, Spectral Imaging Ltd., Oulu, Finland) scan respectively each tealeaves blade at the single band spectrum picture of 14 characteristic wave strong points; 14 characteristic wavelengths are respectively 884nm, 905nm, 915nm, 945nm, 1019nm, 1066nm, 1382nm, 1649nm, 1676nm, 1683nm, 1697nm, 1700nm, 1717nm, 1720nm; The corresponding width single band spectrum picture in each wavelength place, (in figure, only illustrated 4 tealeaves blades) as shown in Figure 1, then adopt GB to measure the polyphenol content of these 120 tealeaves blades, the statistics of the polyphenol content of tealeaves blade is as shown in table 1.
Table 1
Linear relationship according to gray-scale value and the reflectivity of single band spectrum picture, is converted into albedo image by each tealeaves blade at the single band spectrum picture of 14 characteristic wave strong points.
The obtaining step of the gray-scale value of single band spectrum picture and the linear relationship of reflectivity is as follows:
2-1, gather three diffuse reflection on-gauge plates at the benchmark single band spectrum picture of 14 characteristic wave strong points, ask for the gray-scale value of every width benchmark single band image, within the scope of whole visible and near infrared spectrum, the diffuse reflection on-gauge plate adopting the respectively reflectivity of correspondence is 99%, 75% and 2%.
As shown in Figure 2, three diffuse reflection on-gauge plates reflectance curve within the scope of whole visible and near infrared spectrum, in Fig. 2, can find out, the diffuse reflection within the scope of whole visible and near infrared spectrum of three diffuse reflection on-gauge plates is constant separately, for each piece diffuse reflection on-gauge plate, all identical at the reflectivity at all wavelengths place.
As shown in Figure 3, in each characteristic wave strong point, gather the benchmark single band spectrum picture of the diffuse reflection on-gauge plate with different reflectivity, in Fig. 3, the diffuse reflection on-gauge plate that the corresponding reflectivity of R99 is 99%; The diffuse reflection on-gauge plate that the corresponding reflectivity of R75 is 75%; The diffuse reflection on-gauge plate that the corresponding reflectivity of R02 is 2%.
The corresponding gray-scale value of each width benchmark single band spectrum picture, as shown in Figure 4, three gray-scale values of each characteristic wave strong point from left to right successively corresponding reflectivity be the benchmark single band spectrum picture of 99%, 75% and 2% diffuse reflection on-gauge plate.
2-2, for each characteristic wavelength, the gray-scale value of corresponding benchmark single band image and reflectivity are carried out to linear fit, obtain the linear relationship of gray-scale value and reflectivity.
For each characteristic wavelength, there are corresponding three groups of gray-scale values and reflectance value, these three groups of gray-scale values and reflectance value are carried out to linear fit, obtain the linear relationship of gray-scale value and reflectance value.
For example, wavelength be the gray-scale value at 1019nm place and the linear relationship of reflectivity as shown in Figure 5, wavelength be the gray-scale value at 1700nm place and the linear relationship of reflectivity as shown in Figure 6, in Fig. 5, Fig. 6, the diffuse reflection on-gauge plate that the corresponding reflectivity of R99 is 99%; The diffuse reflection on-gauge plate that the corresponding reflectivity of R75 is 75%; The diffuse reflection on-gauge plate that the corresponding reflectivity of R2 is 2%.
The gray-scale value at the different characteristic wavelength place setting up and the linear relationship of reflectivity are respectively:
Y
884＝-140.0781+2.1850x
884
Y
905＝-98.3355+1.5140x
905
Y
915＝-84.9478+1.2915x
915
Y
945＝-13.4568+0.1958x
945
Y
1019＝-6.7178+0.0918x
1019
Y
1066＝-5.1557+0.0682x
1066
Y
1382＝-4.8008+0.0464x
1382
Y
1649＝-7.5836+0.0804x
1649
Y
1676＝-28.5770+0.3714x
1676
Y
1683＝-38.2493+0.5030x
1683
Y
1697＝-64.4862+0.8836x
1697
Y
1700＝-74.9443+1.0215x
1700
Y
1717＝-150.5751+2.0665x
1717
Y
1720＝-165.0176+2.2890x
1720
In formula: x
bgray-scale value for b nm characteristic wave strong point;
Y
breflectivity for b nm characteristic wave strong point.
Gray-scale value based on 14 characteristic wave strong points and the relation of reflectivity, can be the single band spectrum picture of a tealeaves blade to be measured (site on the corresponding tealeaves blade of each pixel difference in single band spectrum picture, each pixel has different gray-scale values) be converted to albedo image, reflectivity corresponding to each pixel in albedo image.
Utilize GB to carry out polyphenol content detection to each tealeaves blade, the polyphenol content obtaining is the average polyphenol content of whole tealeaves blade, albedo image based on each tealeaves blade, after average, obtain the average reflectance of each tealeaves blade, utilize relation that average polyphenol content and average Reflectance curve fitting obtain average polyphenol content and average reflectance as shown in the formula shown in (I)
Y'＝4.004+0.01549λ'
884-0.04241λ'
905-0.002961λ'
915+0.02177λ'
945+0.05390λ'
1019-0.04165λ'
1066+0.02199λ'
1382-0.04560λ'
1649-0.07836λ'
1676+?（I）0.09637λ'
1683-0.02560λ'
1697+0.02705λ'
1700+0.01990λ'
1717-0.02124λ'
1720
In formula (I): λ '
arepresent the average reflectance of the albedo image of a nm characteristic wave strong point;
Y' represents the average polyphenol content at corresponding average reflectance place.
The formula (I) of utilizing average reflectance and average polyphenol content matching to obtain has been expressed the relation of average reflectance with average polyphenol content, fit procedure as shown in Figure 7, formula (I) has also been reacted the relation of each pixel place reflectivity and polyphenol content, obtains formula (II) as follows: Y according to formula (I)
polyphenol content=4.004+0.01549 λ
884-0.04241 λ
905-0.002961 λ
915+ 0.02177 λ
945+ 0.05390 λ
1019-0.04165 λ
1066+ 0.02199 λ
1382-0.04560 λ
1649-0.07836 λ
1676+ (II) 0.09637 λ
1683-0.02560 λ
1697+ 0.02705 λ
1700+ 0.01990 λ
1717-0.02124 λ
1720
In formula (II): λ
arepresent in the albedo image of a nm characteristic wave strong point the reflectivity of a certain pixel;
Y
polyphenol contentrepresent the polyphenol content at respective pixel point place.
The calculating of polyphenol content will be carried out in the corresponding reflectivity substitution of each pixel formula (II) in albedo image, obtain the polyphenol content at each the pixel place in tealeaves leaf image to be measured, and then draw accordingly the polyphenol content distribution plan of tealeaves blade, obtain the polyphenol content distributed intelligence at tealeaves blade each point place, as shown in Figure 8.
Utilize the inventive method 120 tealeaves blades to be detected to polyphenol content (the average polyphenol content that this polyphenol content is each tealeaves blade of the sample prediction obtaining, to in average reflectance substitution formula (I), try to achieve) be illustrated in fig. 9 shown below with the distribution of the actual polyphenol content of sample that utilizes national standard method to detect, the coefficient of determination is 0.925, root-mean-square error is 1.1299, in Fig. 9, can find out, the predicting the outcome of detection method that this patent proposes is high correlation with the measured value of GB detection method.
Comparative example 1
Choose 14 characteristic wavelengths, be respectively 883nm, 904nm, 914nm, 944nm, 1018nm, 1065m, 1381nm, 1648nm, 1675nm, 1682nm, 1696nm, 1699nm, 1716nm and 1719nm, and the relation of setting up in the same manner polyphenol content and reflectivity based on these 14 characteristic wavelengths is as shown in the formula (III):
Y
polyphenol content=0.353-0.000892 λ
883-0.0229 λ
904-0.02273 λ
914+ 0.009645 λ
944+ 0.07 λ
1018-0.04572 λ
1065+ 0.05977 λ
1381-0.07613 λ
1648-0.006481 λ
1675-(III) 0.04603 λ
1682+ 0.109 λ
1696-0.03927 λ
1699-0.02315 λ
1716+ 0.03502 λ
1719
In formula (III): λ
arepresent in the albedo image of a nm characteristic wave strong point the reflectivity of a certain pixel;
Y
polyphenol contentrepresent the polyphenol content at respective pixel point place.
At 14 characteristic wavelengths (883nm, 904nm, 914nm, 944nm, 1018nm, 1065m, 1381nm, 1648nm, 1675nm, 1682nm, 1696nm, 1699nm, 1716nm and 1719nm) locate to obtain the single band spectrum picture of tealeaves blade, and based on formula (III), calculate the average polyphenol content of tealeaves, and being illustrated in fig. 10 shown below with the distribution of the actual polyphenol content of sample that utilizes national standard method to detect, the coefficient of determination is 0.846.
Comparative example 2
Choose 14 characteristic wavelengths, be respectively 886nm, 907nm, 917nm, 947nm, 1021nm, 1068m, 1384nm, 1651nm, 1678nm, 1685nm, 1699nm, 1702nm, 1719nm and 1722nm, and the relation of setting up in the same manner polyphenol content and reflectivity based on these 14 characteristic wavelengths is suc as formula shown in (IV):
Y
polyphenol content=13.320-0.01582 λ
886-0.005859 λ
907-0.04407 λ
917+ 0.155 λ
947-0.08346 λ
1021-0.01333 λ
1068+ 0.02719 λ
1384-0.08262 λ
1651+ 0.03426 λ
1678(IV)+0.01414 λ
1685-0.02472 λ
1699+ 0.01572 λ
1702-0.01421 λ
1719+ 0.0317 λ
1722
In formula (IV): λ
arepresent in the albedo image of a nm characteristic wave strong point the reflectivity of a certain pixel;
Y
polyphenol contentrepresent the polyphenol content at respective pixel point place.
At 14 characteristic wavelengths (886nm, 907nm, 917nm, 947nm, 1021nm, 1068m, 1384nm, 1651nm, 1678nm, 1685nm, 1699nm, 1702nm, 1719nm and 1722nm) locate to obtain the single band spectrum picture of tealeaves blade, and based on formula (IV), calculate the average polyphenol content of tealeaves, and being illustrated in fig. 11 shown below with the distribution of the actual polyphenol content of sample that utilizes national standard method to detect, the coefficient of determination is 0.866.
Result by embodiment 1 and comparative example 1,2, whether selected characteristic wavelength accurately has material impact for detecting polyphenol content, the present invention is by choosing suitable characteristic wavelength, obtained the very high testing result of the coefficient of determination, for carrying out fast the quantitative and detection and localization of tealeaves polyphenol content.
Claims (5)
1. a detection method for Tea Polyphenols in Tea content, is characterized in that, comprises the following steps:
(1) gather tealeaves blade to be measured at the single band spectrum picture of 14 characteristic wave strong points; Described 14 characteristic wavelengths are respectively 884nm, 905nm, 915nm, 945nm, 1019nm, 1066nm, 1382nm, 1649nm, 1676nm, 1683nm, 1697nm, 1700nm, 1717nm, 1720nm;
(2) according to the linear relationship of gray-scale value and the reflectivity of single band spectrum picture, the single band spectrum picture in step (1) is converted into albedo image;
(3) according to following formula, calculate the polyphenol content of each pixel in the albedo image of tealeaves blade;
Y
polyphenol content=4.004+0.01549 λ
884-0.04241 λ
905-0.002961 λ
915+ 0.02177 λ
945+ 0.05390 λ
1019-0.04165 λ
1066+ 0.02199 λ
1382-0.04560 λ
1649-0.07836 λ
1676+ 0.09637 λ
1683-0.02560 λ
1697+ 0.02705 λ
1700+ 0.01990 λ
1717-0.02124 λ
1720
In formula: λ
arepresent in the albedo image of a nm characteristic wave strong point the reflectivity of a certain pixel;
Y
polyphenol contentrepresent the polyphenol content at respective pixel point place.
2. the detection method of Tea Polyphenols in Tea content as claimed in claim 1, is characterized in that, in described step (2), the obtaining step of the gray-scale value of single band spectrum picture and the linear relationship of reflectivity is as follows:
2-1, gather at least three diffuse reflection on-gauge plates at the benchmark single band spectrum picture of 14 characteristic wave strong points, ask for the gray-scale value of every width benchmark single band image, within the scope of visible and near infrared spectrum, the diffuse reflection on-gauge plate adopting has constant separately reflectivity;
2-2, for each characteristic wavelength, the gray-scale value of corresponding benchmark single band image and reflectivity are carried out to linear fit, obtain the linear relationship of gray-scale value and reflectivity.
3. the detection method of Tea Polyphenols in Tea content as claimed in claim 2, is characterized in that, described diffuse reflection on-gauge plate is three～six.
4. the detection method of Tea Polyphenols in Tea content as claimed in claim 3, is characterized in that, described diffuse reflection on-gauge plate is three, is respectively 99% diffuse reflection on-gauge plate, 75% diffuse reflection on-gauge plate and 2% diffuse reflection on-gauge plate.
5. the detection method of Tea Polyphenols in Tea content as claimed in claim 4, is characterized in that, the gray-scale value at different characteristic wavelength place and the linear relationship of reflectivity are respectively:
Y
884＝-140.0781+2.1850x
884
Y
905＝-98.3355+1.5140x
905
Y
915＝-84.9478+1.2915x
915
Y
945＝-13.4568+0.1958x
945
Y
1019＝-6.7178+0.0918x
1019
Y
1066＝-5.1557+0.0682x
1066
Y
1382＝-4.8008+0.0464x
1382
Y
1649＝-7.5836+0.0804x
1649
Y
1676＝-28.5770+0.3714x
1676
Y
1683＝-38.2493+0.5030x
1683
Y
1697＝-64.4862+0.8836x
1697
Y
1700＝-74.9443+1.0215x
1700
Y
1717＝-150.5751+2.0665x
1717
Y
1720＝-165.0176+2.2890x
1720
In formula: x
bgray-scale value for b nm characteristic wave strong point;
Y
breflectivity for b nm characteristic wave strong point.
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| CN105158192A (en) * | 2015-08-31 | 2015-12-16 | 浙江大学 | Detecting system and detecting method for lignin content in moso bamboos |
| CN105158192B (en) * | 2015-08-31 | 2018-06-01 | 浙江大学 | The detecting system and method for content of lignin in a kind of mao bamboon |
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