Abstract
The roles of dissolved organic matter (DOM) in microbial processes and nutrient cycles depend on its composition, which requires detailed measurements and analyses. We introduce a package for R, called staRdom (“spectroscopic analysis of DOM in R”), to analyze DOM spectroscopic data (absorbance and fluorescence), which is key to deliver fast insight into DOM composition of many samples. staRdom provides functions that standardize data preparation and analysis of spectroscopic data and are inspired by practical work. The user can perform blank subtraction, dilution correction, Raman normalization, scatter removal and interpolation, and fluorescence normalization. The software performs parallel factor analysis (PARAFAC) of excitation–emission matrices (EEMs), including peak picking of EEMs, and calculates fluorescence indices, absorbance indices, and absorbance slope indices from EEMs and absorbance spectra. A comparison between PARAFAC solutions by staRdom in R compared with drEEM in MATLAB showed nearly identical solutions for most datasets, although different convergence criteria are needed to obtain similar results and interpolation of missing data is important when working with staRdom. In conclusion, staRdom offers the opportunity for standardized multivariate decomposition of spectroscopic data without requiring software licensing fees and presuming only basic R knowledge.
Highlights
Dissolved organic matter (DOM) is the dominant organic matter form in most aquatic ecosystems, where it modifies a plethora of ecosystem processes [1]
Because the parallel factor analysis (PARAFAC) decomposition depends on the number of components N and this value is chosen by the user, finding an appropriate number N is an important task during the analysis
We compared the results from multiple PARAFAC models using staRdom (PARAFAC model calculated by the multiway package) and drEEM (PARAFAC model calculated by the N-way toolbox)
Summary
Dissolved organic matter (DOM) is the dominant organic matter form in most aquatic ecosystems, where it modifies a plethora of ecosystem processes [1]. Three-dimensional excitation–emission matrices (EEMs) represent the spectroscopic measurements of DOM best [28], showing the complex picture of different, partially overlapping wavelengths of fluorescent light from various DOM molecules Such EEMs cover a wide range of excitation and emission wavelengths (between approximately 200 and 700 nm) and can have more than 3000 data points per sample (e.g., [20]). We present and test a new package for fast and comprehensive spectroscopic analysis of DOM in R, called staRdom (“spectroscopic analysis of DOM in R”), which is suitable for the demands of both beginners and experienced users This package combines and extends existing R packages, namely the multiway package [38] for PARAFAC and the eemR package [47] for data preparation and index calculation and provides additional ways for EEM data preparation and absorbance data analysis. PARAFAC model results and the performance between staRdom (which uses the multiway package for model fitting) and drEEM (which uses the N-way toolbox for model fitting)
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