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Nitrate Nitrogen Quantification via Ultraviolet Absorbance: A Case Study in Agricultural and Horticultural Regions in Central China

Yiheng Zang Orcid Logo, Jing Chen, Muhammad Awais, Mukhtar Iderawumi Abdulraheem Orcid Logo, Moshood Abiodun Yusuff Orcid Logo, Kuan Geng, Yongqi Chen, Yani Xiong, Linze Li, Yanyan Zhang, Vijaya Raghavan Orcid Logo, Jiandong Hu Orcid Logo, Junfeng Wu, Guoqing Zhao Orcid Logo

Agriculture, Volume: 15, Issue: 11, Start page: 1131

Swansea University Author: Guoqing Zhao Orcid Logo

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DOI (Published version): 10.3390/agriculture15111131

Abstract

Soil nitrate nitrogen (NO3−-N) is a key indicator of agricultural non-point source pollution. The ultraviolet (UV) dual-wavelength method is widely used for NO3−-N detection, but interference from complex soil organic matter affects its accuracy. This study investigated how organic matter influences...

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Published in: Agriculture
ISSN: 2077-0472
Published: MDPI AG 2025
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URI: https://cronfa.swan.ac.uk/Record/cronfa69670
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This study investigated how organic matter influences NO3&#x2212;-N detection by optimizing UV dual-wavelength combinations. Density functional theory (DFT) calculations showed slight spectral broadening of fulvic and humic acids in the presence of NO3&#x2212;-N under UV spectrum. Standard solutions and soil samples were used to compare the detection performance of different wavelength pairs. The findings indicated that the dual-wavelength combination of 235 nm/275 nm is optimal rather than 220 nm/275 nm for measuring soil samples at NO3&#x2212;-N concentrations exceeding 5 mg&#xB7;L&#x2212;1. The 235/275 nm method gave an average calibration coefficient of 1.57. Compared to the national standard and flow analysis methods, the average relative errors were 19.7% and 22.3% (p &lt; 0.001), respectively, indicating its suitability for practical soil applications. 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spelling 2025-06-10T11:35:43.3664008 v2 69670 2025-06-10 Nitrate Nitrogen Quantification via Ultraviolet Absorbance: A Case Study in Agricultural and Horticultural Regions in Central China 2ff29aa347835abe2af6d98fa89064b4 0009-0003-9537-9016 Guoqing Zhao Guoqing Zhao true false 2025-06-10 CBAE Soil nitrate nitrogen (NO3−-N) is a key indicator of agricultural non-point source pollution. The ultraviolet (UV) dual-wavelength method is widely used for NO3−-N detection, but interference from complex soil organic matter affects its accuracy. This study investigated how organic matter influences NO3−-N detection by optimizing UV dual-wavelength combinations. Density functional theory (DFT) calculations showed slight spectral broadening of fulvic and humic acids in the presence of NO3−-N under UV spectrum. Standard solutions and soil samples were used to compare the detection performance of different wavelength pairs. The findings indicated that the dual-wavelength combination of 235 nm/275 nm is optimal rather than 220 nm/275 nm for measuring soil samples at NO3−-N concentrations exceeding 5 mg·L−1. The 235/275 nm method gave an average calibration coefficient of 1.57. Compared to the national standard and flow analysis methods, the average relative errors were 19.7% and 22.3% (p < 0.001), respectively, indicating its suitability for practical soil applications. These results demonstrate the method’s potential for rapid and accurate NO3−-N detection in real soil samples, supporting its application in environmental monitoring and agricultural management. Journal Article Agriculture 15 11 1131 MDPI AG 2077-0472 nitrate nitrogen in soil; ultraviolet dual-wavelength; agricultural non-point source pollution (ANPS); soil organic matter; calibration coefficient 23 5 2025 2025-05-23 10.3390/agriculture15111131 COLLEGE NANME Management School COLLEGE CODE CBAE Swansea University Another institution paid the OA fee This work was supported by the 14th Five-Year National Key Research and Development Program (2024YFD17000802, 2021YFD1700904), the Major Science and Technology Projects of Henan Province (221111320700), and Henan Center for Outstanding Overseas Scientists (GZS2021007). 2025-06-10T11:35:43.3664008 2025-06-10T11:28:47.0110286 Faculty of Humanities and Social Sciences School of Management - Business Management Yiheng Zang 0009-0007-1732-0229 1 Jing Chen 2 Muhammad Awais 3 Mukhtar Iderawumi Abdulraheem 0000-0002-6745-378X 4 Moshood Abiodun Yusuff 0000-0002-0917-8396 5 Kuan Geng 6 Yongqi Chen 7 Yani Xiong 8 Linze Li 9 Yanyan Zhang 10 Vijaya Raghavan 0000-0003-1819-6710 11 Jiandong Hu 0000-0002-1944-2840 12 Junfeng Wu 13 Guoqing Zhao 0009-0003-9537-9016 14 69670__34446__f187f1febe974c5ea047cd91a893edee.pdf agriculture-15-01131-v2.pdf 2025-06-10T11:28:46.9869924 Output 5877920 application/pdf Version of Record true © 2025 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. true eng https://creativecommons.org/licenses/by/4.0/
title Nitrate Nitrogen Quantification via Ultraviolet Absorbance: A Case Study in Agricultural and Horticultural Regions in Central China
spellingShingle Nitrate Nitrogen Quantification via Ultraviolet Absorbance: A Case Study in Agricultural and Horticultural Regions in Central China
Guoqing Zhao
title_short Nitrate Nitrogen Quantification via Ultraviolet Absorbance: A Case Study in Agricultural and Horticultural Regions in Central China
title_full Nitrate Nitrogen Quantification via Ultraviolet Absorbance: A Case Study in Agricultural and Horticultural Regions in Central China
title_fullStr Nitrate Nitrogen Quantification via Ultraviolet Absorbance: A Case Study in Agricultural and Horticultural Regions in Central China
title_full_unstemmed Nitrate Nitrogen Quantification via Ultraviolet Absorbance: A Case Study in Agricultural and Horticultural Regions in Central China
title_sort Nitrate Nitrogen Quantification via Ultraviolet Absorbance: A Case Study in Agricultural and Horticultural Regions in Central China
author_id_str_mv 2ff29aa347835abe2af6d98fa89064b4
author_id_fullname_str_mv 2ff29aa347835abe2af6d98fa89064b4_***_Guoqing Zhao
author Guoqing Zhao
author2 Yiheng Zang
Jing Chen
Muhammad Awais
Mukhtar Iderawumi Abdulraheem
Moshood Abiodun Yusuff
Kuan Geng
Yongqi Chen
Yani Xiong
Linze Li
Yanyan Zhang
Vijaya Raghavan
Jiandong Hu
Junfeng Wu
Guoqing Zhao
format Journal article
container_title Agriculture
container_volume 15
container_issue 11
container_start_page 1131
publishDate 2025
institution Swansea University
issn 2077-0472
doi_str_mv 10.3390/agriculture15111131
publisher MDPI AG
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
document_store_str 1
active_str 0
description Soil nitrate nitrogen (NO3−-N) is a key indicator of agricultural non-point source pollution. The ultraviolet (UV) dual-wavelength method is widely used for NO3−-N detection, but interference from complex soil organic matter affects its accuracy. This study investigated how organic matter influences NO3−-N detection by optimizing UV dual-wavelength combinations. Density functional theory (DFT) calculations showed slight spectral broadening of fulvic and humic acids in the presence of NO3−-N under UV spectrum. Standard solutions and soil samples were used to compare the detection performance of different wavelength pairs. The findings indicated that the dual-wavelength combination of 235 nm/275 nm is optimal rather than 220 nm/275 nm for measuring soil samples at NO3−-N concentrations exceeding 5 mg·L−1. The 235/275 nm method gave an average calibration coefficient of 1.57. Compared to the national standard and flow analysis methods, the average relative errors were 19.7% and 22.3% (p < 0.001), respectively, indicating its suitability for practical soil applications. These results demonstrate the method’s potential for rapid and accurate NO3−-N detection in real soil samples, supporting its application in environmental monitoring and agricultural management.
published_date 2025-05-23T05:28:48Z
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score 11.444473

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