Rapid and comprehensive grade evaluation of Keemun black tea using efficient multidimensional data fusion

Rapid and comprehensive grade evaluation of Keemun black tea using efficient multidimensional data fusion

To develop a comprehensive evaluation method for Keemun black tea, we used micro-near-infrared spectroscopy, computer vision, and colorimetric sensor array to collect data. We used support vector machine, least-squares support vector machine (LS-SVM), extreme learning machine, and partial least squa...

Full description

Bibliographic Details
Main Authors: Luqing Li, Yurong Chen, Shuai Dong, Jingfei Shen, Shuci Cao, Qingqing Cui, Yan Song, Jingming Ning
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:Food Chemistry: X
Subjects:
Keemun black tea grading
Near-infrared spectroscopy
Computer vision
Colorimetric sensor array
Data fusion
Online Access:http://www.sciencedirect.com/science/article/pii/S259015752300367X

Internet

http://www.sciencedirect.com/science/article/pii/S259015752300367X

Similar Items