Just-in-Time Learning-Integrated Partial Least-Squares Strategy for Accurately Predicting 71 Chemical Constituents in Chinese Tobacco by Near-Infrared Spectroscopy-Reference-Cited by-同舟云学术

Just-in-Time Learning-Integrated Partial Least-Squares Strategy for Accurately Predicting 71 Chemical Constituents in Chinese Tobacco by Near-Infrared Spectroscopy

Published:2022-10-20 Issue:43 Volume:7 Page:38650-38659
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Liang Youyan¹,Zhao Le¹^ORCID,Guo Junwei¹,Wang Hongbo¹,Liu Shaofeng¹,Wang Luoping²,Chen Li¹,Chen Mantang¹,Zhang Nuohan¹,Liu Huimin¹,Nie Cong¹

Affiliation:

1. Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou, Henan450001, China

2. Technology Center of China Tobacco Yunnan Industrial Co. Ltd., Kunming650231, China

Funder

China National Tobacco Corporation

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.2c04139

Reference35 articles.

1. Highly Efficient and Comprehensive Identification of Ethyl Methanesulfonate-Induced Mutations in Nicotiana tabacum L. by Whole-Genome and Whole-Exome Sequencing

2. The Sensory Difference Threshold of Menthol Odor in Flavored Tobacco Determined by Combining Sensory and Chemical Analysis

3. The Chemical Components of Tobacco and Tobacco Smoke

4. Determination of 27 chemical constituents in Chinese southwest tobacco by FT-NIR spectroscopy

5. On-Line Monitoring of the Tobacco Leaf Composition during Flue-Curing by Near-Infrared Spectroscopy and Deep Transfer Learning

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