Wünsch Urban J, Acar Evrim, Koch Boris P, Murphy Kathleen R, Schmitt-Kopplin Philippe, Stedmon Colin A
Chalmers University of Technology, Architecture and Civil Engineering , Water Environment Technology , Sven Hultins Gata 6 , 41296 Gothenburg , Sweden.
National Institute of Aquatic Resources , Technical University of Denmark , Kemitorvet , 2800 Kgs. Lyngby , Denmark.
Anal Chem. 2018 Dec 18;90(24):14188-14197. doi: 10.1021/acs.analchem.8b02863. Epub 2018 Dec 3.
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.
研究溶解有机物（DOM）的生物地球化学需要综合多种互补分析技术的数据。传统的数据综合方法是寻找使用不同仪器对同一样品进行测量之间的相关性。相比之下，数据融合同时将来自多个仪器的数据分解为潜在的共享和非共享成分。在此，先进耦合矩阵和张量分解（ACMTF）被用于识别北极峡湾中DOM荧光组分的分子指纹。ACMTF用六个完全共享的成分解释了99.84%的变异性。单个分子式与多个荧光成分相关联，反之亦然。分子指纹在多样性和海洋学模式上存在差异，这表明与DOM的生物地球化学来源和成岩状态有关。通过ACMTF获得的指纹与传统相关性分析相比更具特异性，并且能提供更深入的组成洞察。多变量数据融合可对齐极其复杂、异质的DOM数据集，从而有助于更全面地理解DOM生物地球化学。
