Issue 7, 2020
From the journal:

Chemical Communications

A color-spectral machine learning path for analysis of five mixed amino acids†

Qiannan Duan, ORCID logo a   Jianchao Lee, ORCID logo *b   Shourong Zheng, ORCID logo a   Jiayuan Chen,b   Run Luo,b   Yunjin Fengb  and  Zhaoyi Xu ORCID logo *a  

* Corresponding authors

a State Key Laboratory of Pollution Control and Resource Reuse, Jiangsu Key Laboratory of Vehicle Emissions Control, School of the Environment, Nanjing University, Nanjing 210023, China
E-mail: zhaoyixu@nju.edu.cn

b Department of Environmental Science, Shaanxi Normal University, Xi’an 710062, China
E-mail: jianchaolee@snnu.edu.cn

Abstract

A machine learning (ML) strategy based on color-spectral images for mixed amino acid (AA) analysis is presented. The results showed that a well-trained ML model could accurately predict multiple AAs at the same time, suggesting its value for facilitating quantitative analysis of mixed AA systems.

Graphical abstract: A color-spectral machine learning path for analysis of five mixed amino acids

About
Cited by
Related
Download options Please wait...

Supplementary files

Article information

DOI
https://doi.org/10.1039/C9CC07186E
Article type
Communication
Submitted
13 Sep 2019
Accepted
09 Dec 2019
First published
11 Dec 2019

Chem. Commun., 2020,56, 1058-1061

Permissions

Request permissions

A color-spectral machine learning path for analysis of five mixed amino acids

Q. Duan, J. Lee, S. Zheng, J. Chen, R. Luo, Y. Feng and Z. Xu, Chem. Commun., 2020, 56, 1058 DOI: 10.1039/C9CC07186E

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements