College of Environment and Ecology, Jiangsu Open University, Nanjing 210017, China.
The State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science Chinese Academy of Sciences, Nanjing 210008, China.
Molecules. 2023 Jan 5;28(2):567. doi: 10.3390/molecules28020567.
Nitrate is a prominent pollutant in water bodies around the world. The isotopes in nitrate provide an effective approach to trace the sources and transformations of nitrate in water bodies. However, determination of isotopic composition by conventional analytical techniques is time-consuming, laborious, and expensive, and alternative methods are urgently needed. In this study, the rapid determination of NO in water bodies using Fourier transform infrared attenuated total reflectance spectroscopy (FTIR-ATR) coupled with a deconvolution algorithm and a partial least squares regression () model was explored. The results indicated that the characteristic peaks of NO/NO mixtures with varied N/N ratios were observed, and the proportion of NO was negatively correlated with the wavenumber of absorption peaks. The models for nitrate prediction of NO/NO mixtures with different proportions were established based on deconvoluted spectra, which exhibited good performance with the ratio of prediction to deviation () values of more than 2.0 and the correlation coefficients () of more than 0.84. Overall, the spectra pretreatment by the deconvolution algorithm dramatically improved the prediction models. Therefore, FTIR-ATR combined with deconvolution and provided a rapid, simple, and affordable method for determination of NO content in water bodies, which would facilitate and enhance the study of nitrate sources and water environment quality management.
硝酸盐是全球水体中的一种主要污染物。硝酸盐中的同位素为追踪水体中硝酸盐的来源和转化提供了一种有效的方法。然而,传统的分析技术在测定同位素组成时既耗时、费力又昂贵,因此迫切需要替代方法。本研究探讨了傅里叶变换衰减全反射红外光谱(FTIR-ATR)结合去卷积算法和偏最小二乘回归(PLS)模型,用于快速测定水体中的 NO。结果表明,观察到了具有不同 N/N 比的 NO/NO 混合物的特征峰,NO 的比例与吸收峰的波数呈负相关。基于去卷积光谱建立了不同比例 NO/NO 混合物的硝酸盐预测模型,其预测偏差比(RPD)值大于 2.0,相关系数(R2)大于 0.84,性能良好。总的来说,去卷积算法的光谱预处理极大地改善了预测模型。因此,FTIR-ATR 结合去卷积和 PLS 为测定水体中的 NO 含量提供了一种快速、简单且经济实惠的方法,这将有助于加强硝酸盐来源和水环境质量的研究。