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\hypersetup{pdftitle={Development of Mid"=Infrared Spectroscopy Based Soil Microbial Pool Partition Indexes for Soil Organic Carbon Turnover Models},pdfauthor={Hieu Linh Duong, Frank Rasche},pdfsubject={Tropentag 2016: Abstract},pdfkeywords={Mid-infrared spectroscopy, soil microbial pool partition indexes, soil organic carbon turnover models},pdfpagemode=None,colorlinks=true}
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\parbox[b]{13.4cm}{\centering \large{\textbf{Tropentag, September 18-21, 2016, Vienna, Austria}}\\[1ex] \Large{``Solidarity in a competing world ---\\fair use of resources''\\[2ex]}}
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\begin{center}
\Large{\textbf{Development of Mid"=Infrared Spectroscopy Based Soil Microbial Pool Partition Indexes for Soil Organic Carbon Turnover Models\footnote{\textbf{Contact Address:} Hieu Linh Duong, Vietnamese-german University, Fraubronnstraße 25, 70599~Stuttgart, Germany, \mbox{e-mail}: \email{duonghieulinh@gmail.com}}\\[0.8ex]}}
\normalsize{\textsc{Hieu Linh Duong$^{1}$, Frank Rasche$^{2}$}}
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\begin{itemize*}
\item[]{\small{\textit{$^{1}$Vietnamese-german University, Germany}}}
\item[]{\small{\textit{$^{2}$University of Hohenheim, Inst. of Agricultural Sciences in the Tropics (Hans-Ruthenberg-Institute), Germany}}}
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\index[author]{Duong, Hieu Linh}
\index[author]{Rasche, Frank}
\begin{center}
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\textbf{Abstract}
\begin{abstract}
\normalsize{
Soil organic matter (SOM) is ecologically important and plays a vital role in agro"=ecosystems. In order to preserve landscapes as well as soil quality for the future, it is necessary to understand the complicated dynamics of SOM at the regional scale. One of the approaches to satisfy this need is to use modelling of SOM such as the frequently used DAISY model. In this model, SOM is split into three main pools, including dead native soil organic matter (SOM), microbial biomass (SMB), and added organic matter (AOM). Each main pool is split into two sub"=pools which are a slow turnover pool (e.g. SOM1, SMB1, and AOM1) and a faster turnover pool (e.g. SOM2, SMB2, and AOM2). The problem of DAISY model is that it is difficult to partition the soil microbial pools and this is considered as a knowledge gap. Hence, this study aims at exploring the microbial pool partition index which is also helpful in assessing the validity of SMB pools. To achieve this objective the first specific goal was to develop and calibrate diffuse reflectance Fourier transform mid"=infrared spectroscopy (midDRIFTS) --based partial least squares regression (PLSR) models to predict the activities of soil enzymes such as $\beta$-D-glucosidase representing the fast turnover pool (SMB2) and phenoloxidase and/or xylanase representing the slow turnover pool (SMB1). This approach was tested at the regional scale, where the two study regions Kraichgau and Swabian Alb in Southwest Germany were considered. The analysis was tested for three cases: the Kraichgau case, the Swabian Alb case, and the generic case in which both study regions are taken into account. Under each case, the prediction models were developed based on cross validation and test set validation. After this step, microbial pool partition indexes (i.e., ratio of predicted enzyme activities) were calculated. In general, the index which might be judged as ``successfully predicted'' was $\beta$-glucosidase/Xylanase, while $\beta$-glucosidase/Phenol"=oxidase ratio was ``unsuccessfully predicted''. In addition, the results of this study confirm that the predicted fractions of microbial biomass with a slow turnover in the microbial pool (SMB1) ranged between \mbox{37\,\%} and \mbox{48\,\%}.}

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\noindent \textbf{Keywords:} Mid"=infrared spectroscopy, soil microbial pool partition indexes, soil organic carbon turnover models
\index[key]{Mid"=infrared spectroscopy}
\index[key]{Soil!microbial pool partition indexes}
\index[key]{Soil!organic carbon turnover models}
\end{document}
