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CN101059426A - Method for non-destructive measurement for tea polyphenol content of tea based on near infrared spectrum technology - Google Patents

Method for non-destructive measurement for tea polyphenol content of tea based on near infrared spectrum technology Download PDF

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CN101059426A
CN101059426A CN 200710069114 CN200710069114A CN101059426A CN 101059426 A CN101059426 A CN 101059426A CN 200710069114 CN200710069114 CN 200710069114 CN 200710069114 A CN200710069114 A CN 200710069114A CN 101059426 A CN101059426 A CN 101059426A
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calibration
sample
tea
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何勇
李晓丽
裘正军
陆江峰
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Zhejiang University ZJU
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Abstract

本发明公开了一种基于近红外光谱技术无损测量茶叶中茶多酚含量的方法,首先要建立校正模型,收集茶叶样本作为校正样本集,并扫描得到校正样本集的可见光和近红外光谱(325-2500nm),对得到的光谱数据进行光谱预处理。然后采用国标规定的方法测量校正样本的茶多酚含量。采用多元校正回归算法建立校正样本的近红外光谱与茶多酚含量之间的定量关系,即建立了校正模型。对于待检测的茶叶,只要扫描它们的近红外光谱图,并把经过相应光谱预处理的光谱数据输入到校正模型,经过校正模型的测定即得到了该茶叶的茶多酚含量。整个过程在计算机的控制下,实现数据的采集、存储、显示和处理功能。

Figure 200710069114

The invention discloses a method for non-destructively measuring the content of tea polyphenols in tea leaves based on near-infrared spectroscopy. First, a calibration model is established, and tea samples are collected as a calibration sample set, and the visible light and near-infrared spectra of the calibration sample set are obtained by scanning (325 -2500nm), spectral preprocessing is performed on the obtained spectral data. Then use the method specified in the national standard to measure the content of tea polyphenols in the calibration sample. The quantitative relationship between the near-infrared spectrum of the calibration sample and the content of tea polyphenols was established by using the multivariate calibration regression algorithm, that is, the calibration model was established. For the teas to be detected, just scan their near-infrared spectra, and input the spectral data after corresponding spectral preprocessing into the calibration model, and the tea polyphenol content of the tea can be obtained after the calibration model is measured. The whole process is under the control of the computer to realize the functions of data collection, storage, display and processing.

Figure 200710069114

Description

Method based on polyphenol content in the near-infrared spectrum technique non-destructive measurement for tea
Technical field
The present invention relates to use up the method that learns to do the piecewise analysis material, especially relate to a kind of method based on polyphenol content in the near-infrared spectrum technique non-destructive measurement for tea.
Background technology
Tea Polyphenols (tea polyphenols) is the general name of aldehydes matter and derivant thereof in the tealeaves, accounts for about 16% of tea quality, mainly comprises catechin, flavones, flavonols, anthocyan, leucoanthocyanidin class and phenolic acid and depside.Since its have anti-oxidant, antitumor, anti-ageing, anti-carious tooth, antibiotic, antiviral and hypotensive, transfer blood fat, extensive and definite notable biological activity such as hypoglycemic, so the content of Tea Polyphenols has become the important indicator of tea leaf quality in the tealeaves.Traditional Tea Polyphenols measuring method has: high performance liquid chromatography, capillary electrophoresis, fluoroscopic examination, chemiluminescence detection, mass spectrometry, hydrogen nuclear magnetic resonance etc.It is exactly the measuring process complexity that these methods have individual common characteristic, expend the plenty of time, need chemical reagent and sample need do destructive pre-service.These all are unfavorable for the online detection and the circulation of commodity.Need the content of Tea Polyphenols in a kind of simple, quick, nondestructive method, the real-time detection tealeaves.
Summary of the invention
In order to realize the content of Tea Polyphenols in simple, quick, nondestructive, the real-time detection tealeaves, the purpose of this invention is to provide a kind of method, can carry out quick, accurate, nondestructive on-line measurement Tea Polyphenols in the tea tree based on polyphenol content in the near-infrared spectrum technique non-destructive measurement for tea.
The technical solution used in the present invention is that the step of this method is as follows:
1) foundation of correcting sample light harvesting spectrum; At first will be at different cultivars, different manufacture crafts, different results are collected representational tealeaves sample and set up the calibration samples collection periods; The sample that calibration samples is concentrated uses spectrometer to carry out spectral scan and obtains calibration samples collection standard spectrum then; Same sample needs repeatedly duplicate measurements, and is approximate as this sample standard spectrum with averaged spectrum;
2) correction of spectrum and pre-service; The first step behind the acquisition sample spectrum is that correcting sample light harvesting spectrum is proofreaied and correct and pre-service; Offset the quality of background interference and raising spectrum; Here adopt level and smooth, centralization, differentiate or normalization preprocessing procedures; Pre-service amplifies the original signal difference of hiding out, improves the resolution of spectrum;
3) set up calibration model for the Standard China Green Tea polyphenol content measured value of pretreated spectroscopic data and correcting sample collection by the multiple regression algorithm:
Modern multiple regression algorithm comprises that polynary linear regression algorithm and the especially polynary non-linear regression algorithm of polynary non-linear regression algorithm can carry out match at ubiquitous non-linear phenomenon in the production reality, and set up non-linear regression, so it is very important selecting characteristic wave bands, method commonly used is that the method that progressively returns is sought characteristic wave bands, or the method for regression curve analysis realizes;
4) the forecast sample polyphenol content is measured;
At first scan sample to be predicted and obtain spectrum, the measuring condition that is adopted when obtaining spectrum, the measuring condition that is adopted in the time of must obtaining standard correction collection sample spectrum together is consistent, and these measuring conditions comprise the method for sampling, resolution, sweep spacing or sweep time; The spectrum of forecast sample after spectrum correction and pre-service, is sent into the polyphenol content that calibration model can be measured unknown sample to spectrum characteristics.
So the present invention just can test that tealeaves to unknown polyphenol content carries out fast, harmless, real-time, online mensuration as long as set up calibration model on the basis of representational tealeaves sample.
The present invention compares with background technology, and the beneficial effect that has is:
1) utilize polyphenol content in the spectrum technology determining tealeaves, its analysis speed is accelerated greatly.The mensuration process of spectrum generally can be finished (multichannel instrument can be finished) in 1 second in 30 seconds.
2) do not use any chemical reagent, reduced the detection cost, also free from environmental pollution.
3) can handle the great amount of samples analysis, save time, detection technique can be good at being applied to producing in real time.
4) can carry out nondestructive measurement to analyzing samples, the still edible and sale of the tealeaves after the measurement.
Description of drawings
Accompanying drawing is the structural principle block diagram that the spectral technique quick nondestructive is measured the method for polyphenol content in the tealeaves
Embodiment
Harvester comprises compositions such as the supporting Halogen lamp LED of near infrared spectrometer, spectrometer, computing machine, standard correction plate, sample inlet pool, power supply.This spectrometer wavelength is 325~2500nm.With data line spectrometer is linked to each other with the PC computer, sample places special glass sample container.In the heart angle is 45 degree in spectrometer probe and the sample container.Treat that spectrum data gathering finishes, carry out Data Management Analysis with spectrum dedicated analysis software ASD ViewSpec ProV2.14 and Unscramble V9.2.
Whole implementation process of the present invention is as shown in drawings:
1. the foundation of calibration samples light harvesting spectrum.At first collect different cultivars, different manufacture crafts, the tealeaves sample of different results period (spring tea, summer tea, autumn tea) is set up the calibration samples collection; The sample utilization spectrometer that calibration samples is concentrated carries out the spectrum that spectral scan obtains the calibration samples collection then; Same sample duplicate measurements 5 times, approximate with averaged spectrum as this sample standard spectrum; Spectrometer is changed data through A/D, obtain spectral data.
2. the pre-service of spectrum.Should pre-service behind the acquisition sample spectrum.The preprocess method of spectrum has smoothly, centralization, differentiate, normalization, polynary scatter correction, small echo denoising or the like.Adopt the sort of preprocess method to select according to the quality of spectrum and the situation of interference, pre-service also can amplify the original signal difference of hiding out, improves the resolution of spectrum, makes spectral information directly perceived more, reliable.In the preprocess method of utilization spectrum, can be the independent use of a certain method of said method, also can be being used in combination of above-mentioned several method.
3. the foundation of calibration model.The calibration samples collection comes the polyphenol content of each sample of measurement update sample set at once through the GB measuring method that adopts polyphenol content after the spectral measurement.National standard method polyphenol content measured value for pretreated spectroscopic data and calibration samples collection can be set up calibration model by the multiple regression algorithm.Modern multiple regression algorithm comprises polynary linear regression algorithm and polynary non-linear regression algorithm.Polynary linear regression algorithm is as partial least-squares regression method, and principal component regression progressively returns etc., be mainly used to handle can linear match data.Polynary non-linear regression algorithm is as artificial neural network, support vector machine etc., and especially polynary non-linear regression algorithm can carry out match at ubiquitous non-linear phenomenon in the production reality, and set up non-linear regression.The data of spectrum generally all have hundreds of to thousands of data points, and all data all are used for setting up model and often cause the model learning time long, problems such as model structure complexity.So it is very important selecting characteristic wave bands, method commonly used is that the method that progressively returns is sought characteristic wave bands, or the method for regression curve analysis realizes.
4. predict sample polyphenol content mensuration; At first scan sample to be predicted and obtain spectrum with spectrometer, measuring method that is adopted when obtaining forecast sample spectrum and condition must be consistent with obtaining the measuring method and the condition that are adopted when the calibration samples light harvesting is composed, such as measurement parameters such as the method for sampling, resolution, sweep spacing or sweep times, should be consistent.The spectrum of forecast sample is carried out the spectrum pre-service, and the method unanimity that pretreated method is adopted in the time of also will composing pre-service with the calibration samples light harvesting is exactly corresponding one by one.Spectrum characteristics is sent into the polyphenol content that calibration model can be measured the prediction sample.
So this method just can test that tealeaves to unknown polyphenol content carries out fast, harmless, real-time, online mensuration as long as set up calibration model on the basis of representational tealeaves sample.

Claims (1)

1、一种基于近红外光谱技术无损测量茶叶中茶多酚含量的方法,其特征在于该方法的步骤如下:1. A method for non-destructively measuring tea polyphenols content in tea leaves based on near-infrared spectroscopy, characterized in that the steps of the method are as follows: 1)校正样品集光谱的建立;首先要收集不同品种,不同制作工艺,不同收获时期的茶叶样本建立校正样本集;然后对校正样本集中的样本运用光谱仪进行光谱扫描得到校正样本集标准光谱;同一样品需多次重复测量,以平均光谱作为该样品标准光谱;1) The establishment of calibration sample set spectrum; firstly, it is necessary to collect tea samples of different varieties, different production processes, and different harvest periods to establish a calibration sample set; then use a spectrometer to perform spectral scanning on the samples in the calibration sample set to obtain the calibration sample set standard spectrum; The sample needs to be measured repeatedly, and the average spectrum is used as the standard spectrum of the sample; 2)光谱的校正与预处理;获得样本光谱后的第一步是对校正样品集光谱进行校正和预处理;抵消背景干扰及提高光谱的质量;这里采用平滑、中心化、求导或归一化光谱预处理方法;预处理把原来隐藏的信号差异放大出来,提高光谱的分辨率;2) Calibration and preprocessing of the spectrum; the first step after obtaining the sample spectrum is to correct and preprocess the spectrum of the calibration sample set; to counteract background interference and improve the quality of the spectrum; here, smoothing, centralization, derivation or normalization are used Optimized spectral preprocessing method; preprocessing amplifies the original hidden signal difference and improves the resolution of the spectrum; 3)对于预处理后的光谱数据和校正样品集的标准茶多酚含量测量值通过多元回归算法来建立校正模型:3) For the preprocessed spectral data and the measured value of the standard tea polyphenol content of the calibration sample set, a calibration model is established through a multiple regression algorithm: 现代的多元回归算法包括多元线形回归算法和多元非线形回归算法尤其是多元非线形回归算法可以针对生产实际中普遍存在的非线形现象进行拟合,并建立非线形回归。同时选择特征波段是非常重要的,常用的方法是逐步回归的方法来寻找特征波段,或者是回归曲线分析的方法来实现;Modern multiple regression algorithms include multiple linear regression algorithms and multiple nonlinear regression algorithms, especially multiple nonlinear regression algorithms, which can fit nonlinear phenomena that are common in production practice and establish nonlinear regression. At the same time, it is very important to select the characteristic bands. The commonly used method is to find the characteristic bands by stepwise regression, or the method of regression curve analysis to achieve; 4)预测样本茶多酚含量测定;4) Determination of tea polyphenol content in the predicted sample; 首先扫描待预测样本获取光谱,获取光谱时所采用的测量条件,必须同获取标准校正集样本光谱时所采用的测量条件保持一致,这些测量条件包括采样方法、分辩率、扫描间隔或扫描时间;把预测样本的光谱经光谱校正及预处理后,把光谱的特征送入校正模型即可测定未知样品的茶多酚含量。First, scan the sample to be predicted to obtain the spectrum. The measurement conditions used to obtain the spectrum must be consistent with the measurement conditions used to obtain the standard calibration set sample spectrum. These measurement conditions include sampling method, resolution, scan interval or scan time; After the spectrum of the predicted sample is corrected and preprocessed, the characteristics of the spectrum are sent to the calibration model to determine the content of tea polyphenols in the unknown sample.
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