Predicting Odor Sensory Attributes of Unidentified Chemicals in Water Using Fragmentation Mass Spectra with Machine Learning Models-Reference-Cited by-同舟云学术

Predicting Odor Sensory Attributes of Unidentified Chemicals in Water Using Fragmentation Mass Spectra with Machine Learning Models

Published:2024-06-15 Issue:26 Volume:58 Page:11504-11513
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Huang Yuanxi¹,Bu Lingjun¹^ORCID,Huang Kuan²,Zhang Huichun³^ORCID,Zhou Shiqing¹^ORCID

Affiliation:

1. Hunan Engineering Research Center of Water Security Technology and Application, Key Laboratory of Building Safety and Energy Efficiency, Ministry of Education, Hunan University, Changsha 410082, China

2. Aropha Inc., Bedford, Ohio 44146, United States

3. Department of Civil and Environmental Engineering, Case Western Reserve University, Cleveland, Ohio 44106, United States

Funder

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.4c01763

Reference57 articles.

1. Water taste and odor (T&O): Challenges, gaps and solutions from a perspective of the WaterTOP network

2. Perceptions of drinking water quality and risk and its effect on behaviour: A cross-national study

3. Data Analytics Determines Co-occurrence of Odorants in Raw Water and Evaluates Drinking Water Treatment Removal Strategies

4. Taste and Odour in Source and Drinking Water: Causes, Controls, and Consequences

5. Variation and removal of 2-MIB in full-scale treatment plants with source water from Lake Tai, China

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