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Ultraviolet Spectroscopic Detection of Nitrate and Nitrite in Seawater Simultaneously Based on Partial Least Squares
A direct, reagent-free, ultraviolet spectroscopic method for the simultaneous determination of nitrate (NO(3)(−)), nitrite (NO(2)(−)), and salinity in seawater is presented. The method is based on measuring the absorption spectra of the raw seawater range of 200–300 nm, combined with partial least s...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8234976/ https://www.ncbi.nlm.nih.gov/pubmed/34208733 http://dx.doi.org/10.3390/molecules26123685 |
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author | Wang, Hu Ju, Aobo Wang, Lequan |
author_facet | Wang, Hu Ju, Aobo Wang, Lequan |
author_sort | Wang, Hu |
collection | PubMed |
description | A direct, reagent-free, ultraviolet spectroscopic method for the simultaneous determination of nitrate (NO(3)(−)), nitrite (NO(2)(−)), and salinity in seawater is presented. The method is based on measuring the absorption spectra of the raw seawater range of 200–300 nm, combined with partial least squares (PLS) regression for resolving the spectral overlapping of NO(3)(−), NO(2)(−), and sea salt (or salinity). The interference from chromophoric dissolved organic matter (CDOM) UV absorbance was reduced according to its exponential relationship between 275 and 295 nm. The results of the cross-validation of calibration and the prediction sets were used to select the number of factors (4 for NO(3)(−), NO(2)(−), and salinity) and to optimize the wavelength range (215–240 nm) with a 1 nm wavelength interval. The linear relationship between the predicted and the actual values of NO(3)(−), NO(2)(−), salinity, and the recovery of spiked water samples suggest that the proposed PLS model can be a valuable alternative method to the wet chemical methods. Due to its simplicity and fast response, the proposed PLS model can be used as an algorithm for building nitrate and nitrite sensors. The comparison study of PLS and a classic least squares (CLS) model shows both PLS and CLS can give satisfactory results for predicting NO(3)(−) and salinity. However, for NO(2)(−) in some samples, PLS is superior to CLS, which may be due to the interference from unknown substances not included in the CLS algorithm. The proposed method was applied to the analysis of NO(3)(−), NO(2)(−), and salinity in the Changjiang (Yangtze River) estuary water samples and the results are comparable with that determined by the colorimetric Griess assay. |
format | Online Article Text |
id | pubmed-8234976 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-82349762021-06-27 Ultraviolet Spectroscopic Detection of Nitrate and Nitrite in Seawater Simultaneously Based on Partial Least Squares Wang, Hu Ju, Aobo Wang, Lequan Molecules Article A direct, reagent-free, ultraviolet spectroscopic method for the simultaneous determination of nitrate (NO(3)(−)), nitrite (NO(2)(−)), and salinity in seawater is presented. The method is based on measuring the absorption spectra of the raw seawater range of 200–300 nm, combined with partial least squares (PLS) regression for resolving the spectral overlapping of NO(3)(−), NO(2)(−), and sea salt (or salinity). The interference from chromophoric dissolved organic matter (CDOM) UV absorbance was reduced according to its exponential relationship between 275 and 295 nm. The results of the cross-validation of calibration and the prediction sets were used to select the number of factors (4 for NO(3)(−), NO(2)(−), and salinity) and to optimize the wavelength range (215–240 nm) with a 1 nm wavelength interval. The linear relationship between the predicted and the actual values of NO(3)(−), NO(2)(−), salinity, and the recovery of spiked water samples suggest that the proposed PLS model can be a valuable alternative method to the wet chemical methods. Due to its simplicity and fast response, the proposed PLS model can be used as an algorithm for building nitrate and nitrite sensors. The comparison study of PLS and a classic least squares (CLS) model shows both PLS and CLS can give satisfactory results for predicting NO(3)(−) and salinity. However, for NO(2)(−) in some samples, PLS is superior to CLS, which may be due to the interference from unknown substances not included in the CLS algorithm. The proposed method was applied to the analysis of NO(3)(−), NO(2)(−), and salinity in the Changjiang (Yangtze River) estuary water samples and the results are comparable with that determined by the colorimetric Griess assay. MDPI 2021-06-16 /pmc/articles/PMC8234976/ /pubmed/34208733 http://dx.doi.org/10.3390/molecules26123685 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Hu Ju, Aobo Wang, Lequan Ultraviolet Spectroscopic Detection of Nitrate and Nitrite in Seawater Simultaneously Based on Partial Least Squares |
title | Ultraviolet Spectroscopic Detection of Nitrate and Nitrite in Seawater Simultaneously Based on Partial Least Squares |
title_full | Ultraviolet Spectroscopic Detection of Nitrate and Nitrite in Seawater Simultaneously Based on Partial Least Squares |
title_fullStr | Ultraviolet Spectroscopic Detection of Nitrate and Nitrite in Seawater Simultaneously Based on Partial Least Squares |
title_full_unstemmed | Ultraviolet Spectroscopic Detection of Nitrate and Nitrite in Seawater Simultaneously Based on Partial Least Squares |
title_short | Ultraviolet Spectroscopic Detection of Nitrate and Nitrite in Seawater Simultaneously Based on Partial Least Squares |
title_sort | ultraviolet spectroscopic detection of nitrate and nitrite in seawater simultaneously based on partial least squares |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8234976/ https://www.ncbi.nlm.nih.gov/pubmed/34208733 http://dx.doi.org/10.3390/molecules26123685 |
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