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Analysis and Model Comparison of Carbon and Nitrogen Concentrations in Sediments of the Yellow Sea and Bohai Sea by Visible-Near Infrared Spectroscopy

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Abstract

Visible-near infrared spectroscopy is considered an effective method for rapidly determining total carbon (TC) and total nitrogen (TN) in terrestrial soils. However, reports on measuring them by VNIR in marine sediments are limited. This article provides an analysis and spectral model comparison of TC and TN in marine sediments using VNIR. The best TC and TN spectral models were established when using the least square support vector machine algorithm with a wavelength, which extended from 226 nm to 975 nm. The prediction results of TN have a high coefficient of determination and residual predictive deviation, providing accurate quantitative predictions. The TC spectral model comes with a disadvantage might due to its usual high concentrations of organic carbon. Characteristic wavelength extraction may lead to the loss of identification information for the characteristics of TC and TN, and full wavelength spectrum contains more information helps more to the quantification.

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Acknowledgements

This work was supported by the Natural Science Foundation of Shandong Province, China (No. ZR2017BB037, ZR2021MD103, ZR2021MD093 and ZR2021QF028) and the National Natural Science Foundation of China (No. 32171578 and U2006209).

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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by [HQ], [PF], [GH] and [XL]. The first draft of the manuscript was written by [HQ]. [YW] assisted in the manuscript revision, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Xueying Li or Yinglong Wang.

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Qiu, H., Fan, P., Hou, G. et al. Analysis and Model Comparison of Carbon and Nitrogen Concentrations in Sediments of the Yellow Sea and Bohai Sea by Visible-Near Infrared Spectroscopy. Bull Environ Contam Toxicol 108, 1124–1131 (2022). https://doi.org/10.1007/s00128-021-03456-5

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  • DOI: https://doi.org/10.1007/s00128-021-03456-5

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