Rapid identification of green tea varieties based on FT-NIR spectroscopy and LDA/QR

Author:

WANG Jiabao1ORCID,WU Xiaohong2,ZHENG Jun3,WU Bin4

Affiliation:

1. Jiangsu University, China

2. Jiangsu University, China; Jiangsu University, China

3. University-Taizhou, China

4. Chuzhou Polytechnic, China

Publisher

FapUNIFESP (SciELO)

Subject

Food Science,Biotechnology

Reference41 articles.

1. Hormonal regulation of health-promoting compounds in tea (Camellia sinensis L.);Ahammed G. J.;Plant Physiology and Biochemistry,2022

2. Near infrared with principal component analysis as a novel analytical approach for nanoparticle technology;Brigger I.;Pharmaceutical Research,2000

3. PCA-SVM method with sliding window for online fault diagnosis of a small pressurized water reactor;Cao H. S.;Annals of Nuclear Energy,2022

4. Simultaneous determination of total polyphenols and caffeine contents of green tea by near-infrared reflectance spectroscopy;Chen Q. S.;Microchemical Journal,2006

5. Feasibility study on identification of green, black and Oolong teas using near-infrared reflectance spectroscopy based on support vector machine (SVM);Chen Q.;Spectrochimica Acta. Part A: Molecular and Biomolecular Spectroscopy,2007

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