Airborne crop diseases pose a serious threat to food security and are responsible for devastating loss of yield and over-reliance on pesticides. Early detection enables farmers to take preventative action, drastically reducing damage and cost. Current detection regimes often rely on expert identification of the pathogen from plant damage. More recently, other molecular techniques have emerged. However, these methods suffer the same problems - being specific for a single species and a need for relatively large quantities of pathogenic material. Recently, TGAC has been working on an approach dubbed Air-seq that seeks to identify pathogens through sequencing of biological particles present in air. This overcomes both problems associated with current techniques as it is unbiased (not limited by species) and requires very small quantities of material. Our ultimate aim is to put sample collection, sequencing and analysis in a single box that can be deployed in the field. Key to success is a compact sequencing technology and this has recently emerged in the form of Oxford Nanopore Technologies' (ONT) MinION. The MinION is a new compact, low-cost sequencing technology that offers long reads (thousands of bases of DNA) and a streamed mode of operation enabling analysis of data as it is generated. These attributes make it ideally suited to in-field use. However, part of the process of generating sequencing data involves converting an electrical signal from the DNA sensing pore into a sequence of bases (letters) and this is performed via an internet 'basecalling' service. For in-field deployment, this is unsatisfactory, as we cannot rely on high speed, reliable data connections. We believe a completely new approach is required in which we utilise the raw signal data in order to identify species, instead of searching against basecalled sequence. In this project, we will develop a tool that searches Nanopore signal data looking for the characteristic signal traces of pathogens of interest, building up a report on abundance levels in the process.