Tea infrared spectrum classification method for fuzzy uncorrelated C means clustering

A technology of infrared spectrum and mean value clustering, which is applied in the direction of material analysis, analysis materials, instruments, etc. through optical means, which can solve the problems of unable to dynamically extract sample identification information, and achieve the effect of improving accuracy and high clustering accuracy

Active Publication Date: 2018-11-23
恩施市朱砂溪生态农业有限公司
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Problems solved by technology

However, the fuzzy C-means clustering FCM cannot dynamically extract the identification information of the samples during the fuzzy clustering process.

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  • Tea infrared spectrum classification method for fuzzy uncorrelated C means clustering
  • Tea infrared spectrum classification method for fuzzy uncorrelated C means clustering
  • Tea infrared spectrum classification method for fuzzy uncorrelated C means clustering

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Embodiment Construction

[0047] The present invention will be further described below in conjunction with the embodiments and accompanying drawings.

[0048] like figure 1 Shown, method of the present invention comprises the steps:

[0049]Step 1. Infrared spectrum collection and spectral pretreatment of tea samples: Turn on the FTIR-7600 Fourier transform infrared spectrometer and preheat it for 1 hour. The number of scans is 32, and the wavenumber range of the spectral scan is 7800cm -1 ~350cm -1 , the scanning interval is 1.928cm -1 , with a resolution of 4cm -1 . Three kinds of high-quality bamboo leaf green tea, low-quality bamboo leaf green tea and Emeishan Maofeng tea were taken as research objects, and appropriate amount of three kinds of tea leaves were ground and pulverized, and then filtered with a 40-mesh sieve, and 0.5g of each was mixed with potassium bromide at a ratio of 1:100. mix. For each sample, 1 g of the mixture was taken for film pressing, and then scanned 3 times with a ...

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Abstract

The invention discloses a tea infrared spectrum classification method for fuzzy uncorrelated C means clustering. By adopting the method, fuzzy uncorrelated authentication information of tea infrared spectrum data can be dynamically extracted in the fuzzy C means clustering process, so that the accuracy of tea variety authentication can be improved. The method comprises the following steps of firstly, collecting an infrared spectrum of a tea sample with a Fourier infrared spectrometric analyzer; then, performing multiplicative scatter correction pretreatment on the infrared spectrum; then, performing dimensionality reduction on spectrum data to 20 dimensions with a main component analysis method; then, utilizing linear discriminant analysis to extract the authentication information in the spectrum data; and finally, performing tea variety classification with a fuzzy uncorrelated C means clustering method. The fuzzy uncorrelated C means clustering method is designed on the basis of a fuzzy C means clustering method, and the tea infrared spectrum classification method for fuzzy uncorrelated C means clustering has the advantages of rapidness in detection speed, rapidness in classification speed, high classification accuracy and the like and can realize correct classification of tea varieties.

Description

technical field [0001] The invention relates to a tea classification method, in particular to a tea infrared spectrum classification method based on fuzzy non-correlation C-mean clustering. Background technique [0002] Drinking tea is the traditional food culture of Chinese people. Tea contains substances beneficial to human health such as tea polyphenols, tea polysaccharides and theanine. At present, there are many varieties of tea in the market, and the importance of tea quality has gradually been paid attention to by people. However, there are so many good and bad teas in the market that it is difficult to distinguish the good from the bad. Therefore, it is very important to develop a fast and effective method for identifying tea varieties. [0003] Infrared spectroscopy is mainly used for qualitative and quantitative analysis of organic compounds. As a non-destructive testing technology, infrared spectroscopy has been widely used in the fields of agricultural produc...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N21/3563
CPCG01N21/3563G01N2021/3595
Inventor 武小红傅海军陈勇武斌孙俊戴春霞翟艳丽
Owner 恩施市朱砂溪生态农业有限公司
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