Assessing Soil Organic Matter (SOM) on a Landscape Scale by Combining Non-Invasive (Spectroscopic) and Invasive Methods

该项目旨在探索VIS-NIR光谱技术在景观水平上确定SOM数量和质量的潜力。为了提供有关SOM的详细信息，我们将结合联合收割机现场光谱与更高分辨率的实验室VIS-NIR，FTIR和拉曼光谱（FTIRS和拉曼检测中红外MIR中SOM的基本分子振动），Py-FIMS（SOM分子组成，热稳定性）和实验室分馏方案（不同稳定性和周转率的SOM池）。化学计量学建模将基于从链中采集的样品，通过二维相关光谱和多块PLS技术整合VIS-NIR和FTIR（拉曼）之间的相关模式。从这一点和概述的处理工作流程（标准样品程序，散射校正，光谱特征选择）的SOM参数的稳定预测模型，预计关闭实验室和现场光谱之间的差距差距。此外，土壤表面的有机质特性（代表性的完整表土，时间变异性）将进行研究，以进一步探索现场光谱的潜力。这旨在改进便携式光谱仪或遥感仪器在SOM评估中的应用。SOM和SOM参数的映射将根据（可能分层）土壤景观方法中的现场光谱读数进行。

The proposed project aims at exploring the potentials of VIS-NIR spectroscopy to determine SOM quantity and quality at landscape level. To provide detailed information on SOM, we will combine in-field spectroscopy with higher resolved laboratory VIS-NIR, FTIR and Raman spectroscopy (FTIRS and Raman to detect fundamental molecular vibrations of SOM in the middle infrared MIR), Py-FIMS (SOM molecular constituents, thermal stability), and laboratory fractionation schemes (SOM pools of different stability and turnover rate). Based on samples taken from catenae, chemometric modelling will integrate correlation patterns between VIS-NIR and FTIR (Raman) by techniques as 2D correlation spectroscopy and multiblock PLS. From this and an outlined processing workflow (standard sample procedure, scatter corrections, spectral feature selection) stable prediction models for SOM parameters are expected, which close the gap between lab and field spectroscopy. Furthermore, SOM properties at soil surfaces (representativeness for the complete topsoil, temporal variability) will be studied to further explore the potentials of field spectroscopy. This aims towards an improved application of portable spectrometers or remote sensing instruments for SOM assessment. Mapping of SOM and SOM parameters will be performed based on in-situ spectral readings in a (maybe stratified) soilscape approach.