Research Projects

India's Northeastern Region (NER) is highly susceptible to climate change due to its geo-ecological fragility and strategic location in the eastern Himalayan region. Droughts and floods are adverse climatic conditions arising from deficit and excess rainfall, respectively. The region's crop system is predominantly rice, which faces various stresses such as drought, heat stress during Rabi season, flood/flash flood, and low light intensity during Karif season. About 98% of rainwater is lost through runoff, and only 2% is utilized due to lack of technology for judicious water application. Automated on-the-go mapping of plant stress could allow for timely intervention and mitigation before critical thresholds are exceeded, thereby maximizing productivity. Hyperspectral and thermal imaging in phenotyping platforms are valuable tools for detecting and discriminating stress, especially over large or sensitive regions. An experiment will be conducted with Kharif and Rabi rice (at least 20 genotypes) using different simulation tools to create various stresses, including high temperature, drought, and submergence stress conditions. Different levels of temperature will be maintained at different stages of crop growth under automated control Temperature gradient tunnel. Water stress will be maintained by withholding water at different stages of crop growth. The proposed study will focus on plant health functions such as crop temperature, chlorophyll fluorescence, photosynthetic energy down regulation, and photosynthetic pigments detected through various remotely sensed platforms to monitor early responses to different stresses. If remotely sensed data can accurately identify specific levels of crop stress, producers can use this information to better assist them in crop management, maximize yields, and protect their investments.