Investigation of sample partitioning in quantitative near-infrared analysis of soil organic carbon based on parametric LS-SVR modeling-Reference-Cited by-同舟云学术

Investigation of sample partitioning in quantitative near-infrared analysis of soil organic carbon based on parametric LS-SVR modeling

Published:2015 Issue:98 Volume:5 Page:80612-80619
ISSN:2046-2069
Container-title:RSC Advances
language:en
Short-container-title:RSC Adv.

Author:

Chen Hua-Zhou¹²³⁴,Shi Kai¹²³⁴,Cai Ken⁵⁶⁷⁴,Xu Li-Li⁸⁹¹⁰⁴,Feng Quan-Xi¹²³⁴

Affiliation:

1. College of Science

2. Guilin University of Technology

3. Guilin 541004

4. China

5. School of Information Science and Technology

6. Zhongkai University of Agriculture and Engineering

7. Guangzhou

8. School of Ocean

9. Qinzhou University

10. Qinzhou

Abstract

A framework for sample partitioning is proposed to take into account the tunable ratio of numbers of calibration and prediction samples, in consideration with the randomness, stability and robustness of calibration models.

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemical Engineering,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2015/RA/C5RA12468A

Reference39 articles.

1. Quantitative monitoring of an activated sludge reactor using on-line UV-visible and near-infrared spectroscopy

2. Non-destructive estimation of moisture, water activity and NaCl at ham surface during resting and drying using NIR spectroscopy

3. FT-NIR spectroscopy for caffeine estimation in instant green tea powder and granules

4. Techniques for quantifying chemicals concealed behind clothing using near infrared spectroscopy

5. NIR spectroscopy to identify and quantify imazapyr in soil

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