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Li Z, Hu Y, Wang L, Liu H, Ren T, Wang C, Li D. Selective and Accurate Detection of Nitrate in Aquaculture Water with Surface-Enhanced Raman Scattering (SERS) Using Gold Nanoparticles Decorated with β-Cyclodextrins. SENSORS (BASEL, SWITZERLAND) 2024; 24:1093. [PMID: 38400251 PMCID: PMC10893249 DOI: 10.3390/s24041093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 01/31/2024] [Accepted: 02/05/2024] [Indexed: 02/25/2024]
Abstract
A surface-enhanced Raman scattering (SERS) method for measuring nitrate nitrogen in aquaculture water was developed using a substrate of β-cyclodextrin-modified gold nanoparticles (SH-β-CD@AuNPs). Addressing the issues of low sensitivity, narrow linear range, and relatively poor selectivity of single metal nanoparticles in the SERS detection of nitrate nitrogen, we combined metal nanoparticles with cyclodextrin supramolecular compounds to prepare a AuNPs substrate enveloped by cyclodextrin, which exhibits ultra-high selectivity and Raman activity. Subsequently, vanadium(III) chloride was used to convert nitrate ions into nitrite ions. The adsorption mechanism between the reaction product benzotriazole (BTAH) of o-phenylenediamine (OPD) and nitrite ions on the SH-β-CD@AuNPs substrate was studied through SERS, achieving the simultaneous detection of nitrate nitrogen and nitrite nitrogen. The experimental results show that BTAH exhibits distinct SERS characteristic peaks at 1168, 1240, 1375, and 1600 cm-1, with the lowest detection limits of 3.33 × 10-2, 5.84 × 10-2, 2.40 × 10-2, and 1.05 × 10-2 μmol/L, respectively, and a linear range of 0.1-30.0 μmol/L. The proposed method provides an effective tool for the selective and accurate online detection of nitrite and nitrate nitrogen in aquaculture water.
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Affiliation(s)
- Zhen Li
- National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Yang Hu
- National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
- Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
| | - Liu Wang
- National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
- Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
| | - Houfang Liu
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Tianling Ren
- School of Integrated Circuit, Tsinghua University, Beijing 100084, China
- Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
| | - Cong Wang
- National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
- Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
| | - Daoliang Li
- National Innovation Center for Digital Fishery, China Agricultural University, Beijing 100083, China
- Key Laboratory of Smart Farming Technologies for Aquatic Animal and Livestock, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100083, China
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
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Li D, Wang T, Li Z, Xu X, Wang C, Duan Y. Application of Graphene-Based Materials for Detection of Nitrate and Nitrite in Water-A Review. SENSORS 2019; 20:s20010054. [PMID: 31861855 PMCID: PMC6983230 DOI: 10.3390/s20010054] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Revised: 12/10/2019] [Accepted: 12/16/2019] [Indexed: 12/14/2022]
Abstract
Nitrite and nitrate are widely found in various water environments but the potential toxicity of nitrite and nitrate poses a great threat to human health. Recently, many methods have been developed to detect nitrate and nitrite in water. One of them is to use graphene-based materials. Graphene is a two-dimensional carbon nano-material with sp2 hybrid orbital, which has a large surface area and excellent conductivity and electron transfer ability. It is widely used for modifying electrodes for electrochemical sensors. Graphene based electrochemical sensors have the advantages of being low cost, effective and efficient for nitrite and nitrate detection. This paper reviews the application of graphene-based nanomaterials for electrochemical detection of nitrate and nitrite in water. The properties and advantages of the electrodes were modified by graphene, graphene oxide and reduced graphene oxide nanocomposite in the development of nitrite sensors are discussed in detail. Based on the review, the paper summarizes the working conditions and performance of different sensors, including working potential, pH, detection range, detection limit, sensitivity, reproducibility, repeatability and long-term stability. Furthermore, the challenges and suggestions for future research on the application of graphene-based nanocomposite electrochemical sensors for nitrite detection are also highlighted.
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Affiliation(s)
- Daoliang Li
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
- China-EU Center for Information and Communication Technologies in Agriculture, China Agricultural University, Beijing 100083, China
- Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, China Agricultural University, Beijing 100083, China
- Beijing Engineering and Technology Research Center for Internet of Things in Agriculture, China Agricultural University, Beijing 100083, China
- Correspondence:
| | - Tan Wang
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
- China-EU Center for Information and Communication Technologies in Agriculture, China Agricultural University, Beijing 100083, China
- Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, China Agricultural University, Beijing 100083, China
- Beijing Engineering and Technology Research Center for Internet of Things in Agriculture, China Agricultural University, Beijing 100083, China
| | - Zhen Li
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
- China-EU Center for Information and Communication Technologies in Agriculture, China Agricultural University, Beijing 100083, China
- Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, China Agricultural University, Beijing 100083, China
- Beijing Engineering and Technology Research Center for Internet of Things in Agriculture, China Agricultural University, Beijing 100083, China
| | - Xianbao Xu
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
- China-EU Center for Information and Communication Technologies in Agriculture, China Agricultural University, Beijing 100083, China
- Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, China Agricultural University, Beijing 100083, China
- Beijing Engineering and Technology Research Center for Internet of Things in Agriculture, China Agricultural University, Beijing 100083, China
| | - Cong Wang
- College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
- China-EU Center for Information and Communication Technologies in Agriculture, China Agricultural University, Beijing 100083, China
- Key Laboratory of Agricultural Information Acquisition Technology, Ministry of Agriculture, China Agricultural University, Beijing 100083, China
- Beijing Engineering and Technology Research Center for Internet of Things in Agriculture, China Agricultural University, Beijing 100083, China
| | - Yanqing Duan
- Business school, University of Bedfordshire, Luton LU1 3BE, UK;
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