Urbi holds a Bachelor of Technology in Genetic Engineering from SRM University, Chennai and a Masters of Science in RNA Sciences from the Universite de Lorraine, France for which she received the Charpak Masters Fellowship.
Professionally Urbi has experience in research and design working at a commercial plant tissue culture company, Sun Agrigenetics Pvt Ltd and has worked as an Assistant Professor in Biotechnology at Parul Institute of Applied Sciences, Parul University. Urbi is currently working as a junior project associate at the Indian Institute of Technology Delhi.
In her spare time Urbi is an avid reader and a trained classical dancer.
The recent advancement in Precision Agriculture which aims to achieve yield maximization with natural resource optimization in farming practices worldwide; has brought the techniques of 'Agri-Photonics' to the forefront. In this regard, the increasing food literacy in consumer market has brought about a sharp increase in the demand of natural and organic food. This rapidly growing sector not only forbid the use of chemical fertilizer and pesticides, but also stresses on the production of naturally occurring genetic variants of a specific crop which might not have maximum yield capacity. Thus, the need of a photonics-based technique to identify various transgenic plant species in a fast, non-invasive and objective manner for easy segregation of plant varieties in consumer agriculture has become paramount. This project will explore the use of spectroscopy and imaging using terahertz (THz) range (3000 - 30 µm in wavelength or 0.1 × 1012 10 × 1012 Hz in frequency) which is an extremely sensitive non-contact, non-invasive technique to sense different transgenic species based on their characteristic biochemical fingerprints. Initially, through systematic extraction of genetic material of various phenotypes of a specific crop and subsequent spectral characterization using THz time domain spectroscopy will yield the biochemical signature map of these phenotypes in THz range. In the second phase, the same genetic variants will be imaged in-vivo in THz range to explore the viability of this Agri-photonic technique towards phenotype identification. Finally, high power THz sources working in a relatively narrow frequency range will be used to target these frequency 'signature' towards achieving higher signal-to-noise in the THz image formation. This is required for high efficiency classification of transgenic species through numerical analysis using artificial neural network type identifiers.View full project details