Fertilizer management in agricultural fields is
an integral component of a sustainable agricultural system for maximizing crop
yields; however, excessive fertilizer usage can cause ecological damage due to
algal blooms and increase the financial burden for farmers. To address the
requirement for fertilizer management in agricultural fields, we have developed
a scalable, cost-effective sensor based on screen-printed electrodes and an
injection molding process for robust encapsulation against biofouling as well
as corrosion at the wire/electrode interface. These sensors can easily be
distributed over a wide area and installed at critical zones to provide
information about fertilizer runoff from agricultural fields. We developed an
injection-molded (IM) nitrate and oxidation and reduction potential (ORP)
sensor array that mimics the form of Lego-like structures and deployed the
sensor array with an integrated automated water collection system for detecting
nitrate and oxygen levels in three sites of critical importance throughout
Indiana. Systematic studies revealed the IM nitrate and ORP sensor’s stable
performance in the ecologically relevant range of nitrate level (0.1 mM to 100
mM) and ORP level (80 mV to 650 mV), and a negligible sensitivity drift of <
10% was observed over one month. In the tensile test, the IM sensors had better
mechanical robustness at the wire/electrode interface as compared with the
conventional printed sensors. The IM sensors were interfaced with a
solar-powered Arduino-based microcontroller unit (MCU) based low power portable
module, which has an 8-channel input for real-time wireless sensor data
transmission to a cloud service and computing system from the sites. The
overall electronic system in the field used ~52 W of energy, which was approximately
the same power that the solar panel produces in a day. The field investigation
demonstrated that both the nitrate and ORP sensors can accurately and
consistently measure nitrate and oxygen levels, respectively, for 30 days with
less than 5% error compared to the measurement recorded by the commercial
probes. This work represents a significant step forward in the development of
low-cost and scalable sensor technologies for water quality monitoring in
agricultural fields while minimizing environmental damage.