The central aim of my postdoctoral project is to establish, test, and refine wet-lab methods for profiling RNA fragments from diverse environmental samples, with a particular focus on consumer food products. RNA molecules are highly dynamic and responsive to environmental conditions, making them valuable indicators of biological activity, contamination, and product quality. However, their inherent instability and the complexity of food matrices pose significant technical challenges. To address this, my work integrates both broad-spectrum and targeted approaches to enable sensitive, reliable, and reproducible detection of RNA fragments across a wide range of sample types. One important component of the project involves applying next-generation sequencing (NGS)-based methods. NGS provides an unbiased and comprehensive view of RNA populations, capturing both abundant and rare species as well as fragmented molecules that are often missed with more conventional techniques. By developing optimized library preparation protocols tailored to complex food samples, I aim to improve the recovery and representation of small and degraded RNA fragments, ensuring that the resulting data accurately reflect the underlying biological signals. This work includes systematic testing of extraction methods, quality control steps, and library construction strategies to identify conditions that maximize yield and data quality. Complementing the sequencing-based approaches, I am also developing and adapting targeted methods such as quantitative PCR (qPCR) and rolling circle amplification. These techniques allow for sensitive and specific detection of selected RNA molecules of interest, relevant to food quality and safety. Targeted methods are particularly useful for validation of sequencing results and for applications where rapid, cost-effective, and high-throughput analysis is required. Rolling circle amplification further offers unique opportunities to amplify and detect circular RNAs or small fragments with high sensitivity, expanding the range of RNA species that can be reliably profiled. The integration of these complementary approaches aims to establish a robust methodological toolkit that can be applied across different food products and environmental contexts. By systematically testing these methods under varying conditions, the project seeks to identify best practices and critical parameters that influence RNA stability, recovery, and detectability. Ultimately, this work will contribute to a deeper understanding of RNA biology in food systems and lay the foundation for innovative applications in food safety monitoring, quality assessment, and environmental RNA research.