Ultrahigh resolution total organic carbon analysis using Fourier Transform Near Infrarred Reflectance Spectroscopy (FT‐NIRS)

Abstract

Fourier transform near infrared reflectance spectroscopy (FT‐NIRS) is a cheap, rapid, and nondestructive method for analyzing organic sediment components. Here, we examine the robustness of a within lake FT‐NIRS calibration using a data set of almost 400 core samples from Lake Suigetsu, Japan, as a means to rapidly reconstruct % total organic carbon (TOC). We evaluate the best spectra pretreatment, examine different statistical approaches, and provide recommendations for the optimum number of calibration samples required for accurate predictions. Results show that the most robust method is based on first‐order derivatives of all spectra modeled with partial least squares regression. We construct a TOC model training set using 247 samples and a validation test set using 135 samples (for test set R2 = 0.951, RMSE = 0.280) to determine TOC and illustrate the use of the model in an ultrahigh resolution (e.g., 1 mm/annual) study of a long sediment core from a climatically sensitive archive.