How well can near infrared reflectance spectroscopy (NIRS) measure sediment organic matter in multiple lakes?

Francisco Javier Ancin-Murguzur,Antony G Brown,John Inge Svendsen,Inger Greve Alsos,Charlotte Clarke,Per Sjøgren

doi:10.1007/s10933-020-00121-5

Abstract

Loss-on-ignition (LOI) is the most widely used measure of organic matter in lake sediments, a variable related to both climate and land-use change. The main drawback for conventional measurement methods is the processing time and hence high labor costs associated with high-resolution analyses. On the other hand, broad-based near infrared reflectance spectroscopy (NIRS) is a time and cost efficient method to measure organic carbon and organic matter content in lacustrine sediments once predictive methods are developed. NIRS-based predictive models are most robust when applied to sediments with properties that are already included in the calibration dataset. To test the potential for a broad applicability of NIRS models in samples foreign to the calibration model using linear corrections, sediment cores from six lakes (537 samples, LOI range 1.03–85%) were used as reference samples to develop a predictive model. The applicability of the model was assessed by sequentially removing one lake from the reference dataset, developing a new model and then validating it against the removed lake. Results indicated that NIRS has a high predictive power (RMSEP < 4.79) for LOI with the need for intercept and slope correction for new cores measured by NIRS. For studies involving many samples, NIRS is a cost and time-efficient method to estimate LOI on a range of lake sediments with only linear bias adjustments for different records.

Highlights

Near infrared reflectance spectroscopy (NIRS) is increasingly included in soil studies to reduce costs and processing time (Chodak 2008)
The dataset covers a large variation in sediment composition, with samples ranging from organic-rich gyttja to Standard normal variate (SNV), derivative 1–2–23
While it is expected that NIRS predictions are most accurate when limited to samples with similar properties to those included in the calibration dataset (Foley et al 1998; Chodak 2008), our study shows that comprehensive models including enough variability in stratigraphy or geographical origin can be applicable to other samples

Summary

Introduction

Near infrared reflectance spectroscopy (NIRS) is increasingly included in soil studies to reduce costs and processing time (Chodak 2008). NIRS is a nondestructive method where a light beam with known spectral properties is directed at a sample and the reflected light is measured in the visible and near infrared region of the light spectrum The principal analytical method, loss on ignition (LOI), which has been used for several decades, is an accurate method to measure soil and sediment organic matter (LOI at 550 °C) and CaCO3 content (LOI at 950 °C) (Dean 1974; Heiri et al 2001) and inexpensive in materials, it is expensive in staff time. Alternative methods using wet oxidation (Walkley–Black method; Heanes 1984) are more expensive and time consuming even when automated, and may over-estimate the actual organic carbon content (Wang et al 2012)

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Conclusion