Comparision of pollen classifications by automated image analyses and sequencing
In recent years, molecular methods have gained great importance in supporting ecological studies. Metabarcoding through high-throughput sequencing devices is an especially useful tool to assess diversity and composition of samples that consist of more than a single species. With these new possibilities, there are also new challenges to be addressed. One is that it is not clear, how well quantifications work with such assessments. On the other hand, also automated image processing is now usable for pollen analyses. The concept of this thesis project is to test different methods for using image and sequencing data, compare the techniques and ideally develop strategies to cross-correct both data types with each other to have well quantified and taxonomically resolved species identifications from this hybrid approach.
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