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Method for quickly identifying tea varieties through near-infrared spectroscopy technology

A near-infrared spectroscopy, near-infrared technology, applied in the field of tea variety identification

Active Publication Date: 2015-12-23
CHUZHOU VOCATIONAL & TECHN COLLEGE
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  • Abstract
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Problems solved by technology

[0006] Aiming at the defects and insufficiencies of the noise clustering method in the prior art, the present invention proposes a fast detection speed, high identification accuracy, green and environmental protection, and can realize accurate identification of tea varieties using near-infrared spectrum technology. A method for identifying tea varieties; thereby solving the problem that the noise clustering method can only cluster data with simple topological structures, and improving the accuracy of noise clustering

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  • Method for quickly identifying tea varieties through near-infrared spectroscopy technology
  • Method for quickly identifying tea varieties through near-infrared spectroscopy technology
  • Method for quickly identifying tea varieties through near-infrared spectroscopy technology

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Embodiment

[0035] Step 1. Collection of near-infrared spectra of tea samples: collecting tea samples of different varieties with a near-infrared spectrometer to obtain near-infrared diffuse reflectance spectra of tea samples.

[0036] Three kinds of tea were collected: high-quality Leshan Zhuyeqing, inferior Leshan Zhuyeqing and Emeishan Maofeng. The number of samples for each tea was 32, totaling 96 samples. All the tea samples were ground and then filtered through a 40-mesh sieve. 0.5 g of each sample was uniformly mixed with potassium bromide at a ratio of 1:100, and 1 g of the mixture was taken for film-pressing treatment. When collecting near-infrared spectra, the laboratory temperature is about 25°C, the relative humidity is about 50%, and the FTIR-7600 Fourier transform near-infrared spectroscopy analyzer is turned on and preheated for 1 hour. The spectrum analyzer scans each tea sample 32 times, and the wavenumber range of the spectrum scan is 4001.569~401.1211cm -1 , the scanni...

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Abstract

The invention provides a method for quickly identifying tea varieties through a near-infrared spectroscopy technology. The method comprises the steps that firstly, near-infrared diffuse reflection spectrum of tea is collected through a near-infrared spectroscopy instrument, dimension reduction treatment is conducted on the high-dimension near-infrared spectrum of the tea through principal component analysis (PCA), the variety classification information of tea spectrum data is extracted through linear discriminant analysis (LDA), and finally, the tea varieties are identified and analyzed through a new generalized noise clustering method. The method is high in detection speed, high in identification accuracy, environmentally friendly and capable of accurately identifying the tea varieties.

Description

technical field [0001] The invention relates to the technical field of a method for identifying tea varieties, in particular to a method for quickly identifying tea varieties using near-infrared spectroscopy. Background technique [0002] Tea is one of the three major beverages in the world. It contains organic substances such as tea polyphenols, protein and amino acids, as well as inorganic substances such as potassium, calcium and magnesium. In good health. Leshan Zhuyeqing is a unique tea brand in Leshan. However, there is a phenomenon of shoddy tea in the tea market, and ordinary consumers cannot distinguish between high-quality famous tea and low-quality tea, and are often deceived. In addition, shoddy and inferior tea leaves have damaged the brand reputation of famous and high-quality teas, violated the rights and interests of consumers, and brought troubles to the marketing of famous and high-quality teas. Therefore, it is very necessary to study a method for identi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/49
Inventor 武斌武小红贾红雯
Owner CHUZHOU VOCATIONAL & TECHN COLLEGE
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