The project IsoSens,’’Isotope fingerprint of oil samples: can remote sensing techniques help verify the origin of biofuel?“ is a collaborative project between the Chair of Material Flow Management and Resource Economy (in German Fachgebiet Stoffstrommanagement und Ressourcenwirtschaft, ) and the Chair of Remote Sensing and Image Analysis (in German Fachgebiet Fernerkundung und Bildanalyse, FG SuR) at FG13 of TU Darmstadt. The project IsoSens serves as an enhancement of the project FG FuB, which is being concurrently implemented at FG SuR. FindHerO
The rapid and ever increasing demand for agricultural commodity for bio-economy has been a trigger for a large-scale deforestation and land use change, which directly and indirectly causes negative impacts on climate change and ecosystems. To control such land use changes, analytical and statistical tools are required to determine the origin of the agricultural commodities, in addition to institutional controls (e.g. sustainability certification). The “FindHerO” project at FB SuR, thus, aims to develop a fingerprinting approach to identify the geographical origin of vegetable oils that are to be used for the production of biodiesel. One of the focuses here is to determine which and to what extent site-specific independent variables influence elemental and isotopic compositions of vegetable oil. Particularly for the FindHerO project, rapeseed and corresponding soil samples from different agricultural fields in Hesse are analyzed in the laboratory and correlations of analytical values are to be investigated using statistical tools.
Certain site-specific independent variables can be obtained not only in the laboratory but also from space. In the project IsoSens, site-specific independent variables determined with the aid of remote sensing techniques will be added to the FindHerO-database. The Chair of FuB is in charge of generating two site-specific independent variables, namely, “soil-moisture” and “land cover” with a high spatial resolution using remote sensing data and image processing techniques. Whereas the Chair of SuR is responsible to investigate the correlations of these additional site-specific independent variables with soil properties, which may influence the soil moisture, as well as with hydrogen isotope composition (δ2H) of rapeseed oil, which may be influenced by soil moisture and land-cover. For the data analysis, SPSS as well as GIS will be applied.
At the end, partners of IsoSens will evaluate whether the soil moisture and land cover information obtained by FG FuB help verify the origin of rapeseed samples. Further, partners will identify additional site-specific variables and data which could improve the quality of individual research outcome.