We propose a new paradigm for data-driven precision agriculture, using bio-convergence-based
functional sensors to directly detect plant stress.
The ever-increasing global population, combined with reducing agricultural efficacy due to climate
change poses a significant challenge to meeting the world’s food requirements. Technological
advances, in particular advances in agricultural sensor technology, have been noted to be one of the
most promising directions in addressing this issue. Bio-convergence-based approaches can help
improve the efficacy of agricultural sensing, whilst maintaining sustainability and cost-effectiveness.
Using these approaches, we propose to develop a novel plant-based biosensor that can report the
health and well-being of plants, using direct sensing of plants’ genetic response to stress. This can
allow for in-vivo, reliable, real-time reporting on the needs of plants, at a lower cost than existing
sensor technologies. We propose to execute this using two major research and development
directions: novel bio-synthetic logic gates for efficient detection of multiple stress parameters, and
novel families of electrochemical sensing interfaces with intrinsic amplification. The development of
the proposed sensors will include mathematical/circuit-based modeling, implementation in plants,
and investigations into practicality for on-field use