Determining the feasibility of photonic noses to improve in-field pest monitoring

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Plants emit low levels of volatile organic compounds (VOCs), which qualitativly and quantitativly change when plants are subjected to biotic stressors such as invertebrate pests and fungal diseases. The specificity and abundance of plant VOC emissions in response to pest and disease infestation can be exploited to develop automated plant health monitoring methods to inform integrated pest management (IPM) decision making. This is important as IPM presents an environmentally sustainable method to enhance agricultural production to meet an ever increasing demand, but it relies on ineffective and time consuming monitoring approaches. Gas chromatography coupled mass spectrometry (GC-MS) is the 'gold standard' method for analysing plant VOC emissions under laboratory conditions, however the cost the cost and environmental sensitivity of this instrumentation make it impractical to be the basis for an automated plant health monitoring platform. Electronic noses offer a potential alternative, but are based on electrochemical sesors that suffer from sensitivity issues, sensor drift/aging effects and lack specificity. These systems are often complimentary rather than stand-alone. A new approach is needed to fulfil demands for better pest and disease monitoring. Complex organic molecules, such as VOCs with low to medium molecular weights, can theoretically be identified by their absorption spectra. However, most spectral 'distinctness' tends to be located in the mid infra-red (MIR) wavelength range of roughly 2000-1000 cm-1 and this has traditionally been difficult to analyse. The proposed project seeks to build an inter-disciplinary research community that can exploit recent developments in photonic sensors, specifically Dual Comb Spectroscopy and optical parametric oscillator technology, alongside probabilistic machine learning techniques to develop a 'photonic nose' based plant health monitoring platform that acts as a foundation for future research and development.