| Literature DB >> 30449083 |
Urban J Wünsch1,2, Evrim Acar3, Boris P Koch4,5, Kathleen R Murphy1, Philippe Schmitt-Kopplin6, Colin A Stedmon2.
Abstract
Investigating the biogeochemistry of dissolved organic matter (DOM) requires the synthesis of data from several complementary analytical techniques. The traditional approach to data synthesis is to search for correlations between measurements made on the same sample using different instruments. In contrast, data fusion simultaneously decomposes data from multiple instruments into the underlying shared and unshared components. Here, Advanced Coupled Matrix and Tensor Factorization (ACMTF) was used to identify the molecular fingerprint of DOM fluorescence fractions in Arctic fjords. ACMTF explained 99.84% of the variability with six fully shared components. Individual molecular formulas were linked to multiple fluorescence components and vice versa. Molecular fingerprints differed in diversity and oceanographic patterns, suggesting a link to the biogeochemical sources and diagenetic state of DOM. The fingerprints obtained through ACMTF were more specific compared to traditional correlation analysis and yielded greater compositional insight. Multivariate data fusion aligns extremely complex, heterogeneous DOM data sets and thus facilitates a more holistic understanding of DOM biogeochemistry.Year: 2018 PMID: 30449083 DOI: 10.1021/acs.analchem.8b02863
Source DB: PubMed Journal: Anal Chem ISSN: 0003-2700 Impact factor: 6.986