Abstract
The assessment of pesticide deposition and spray drift is essential for ensuring efficient application and preventing contamination of off-target areas, which remains a significant environmental and public health concern. Regulatory frameworks also require the quantification of drift potential across different sprayer configurations. However, conventional methodologies used to evaluate deposition and drift are not real-time and are often labour-intensive, time-consuming, and costly. These approaches typically involve large sample handling, multiple transfer steps, and trained personnel for laboratory analysis. To address these limitations, this thesis proposes and evaluates innovative resistive and capacitive sensing approaches that enable fast, accurate, and real-time quantification of spray deposition under controlled and laboratory conditions. The first part of the research introduces a resistive-based method to quantify spray deposition in a wind tunnel using fluorescent tracers. Screen-printed electrodes were integrated into material collectors to measure the deposited mass shortly after application. The resistive estimates were validated against spectrophotometric and gravimetric reference methods. Results showed that both the resistive and spectrophotometric approaches slightly overestimated the deposited mass relative to gravimetric measurements. The resistive system demonstrated strong potential for laboratory testing and future in-field monitoring of spraying equipment. Building upon these findings, the second study refined the resistive-based approach by developing an array of sensors and a multiplexed acquisition system for time-resolved deposition measurements. A multi-point calibration curve enhanced measurement accuracy, while validation against spectrophotometric and gravimetric data confirmed reliability. Wind-tunnel trials conducted with fluorescein and fluorescein combined with potassium chloride tracers showed strong correlations between deposited mass and electrical conductivity. The electrical method demonstrated high accuracy, with mean percentage deviations from the standard spectrophotometric method below 10% for fluorescein and 8% for fluorescein combined with potassium chloride. The workflow enables rapid, sequential measurements across the sensor array and supports scalability towards field deployment for real-time deposition mapping and precision agriculture. The third part of the research presents the design and validation of a low-cost, flexible interdigitated capacitive sensor for real-time quantification of droplet deposition. Controlled volume and laboratory spraying experiments demonstrated strong correlations between the change in capacitance (ΔC) and accumulated volume (Va), as well as between ΔC and surface coverage (Aa). Sensor response was influenced by droplet size and formulation properties, highlighting the need for formulation and droplet specific calibration strategies. Nevertheless, the sensor maintained consistent performance under varying experimental conditions and showed strong potential for integration into monitoring and feedback-controlled spraying systems. Overall, the results of this thesis demonstrate that resistive and capacitive sensing techniques offer fast, reliable, and scalable alternatives to conventional methods for measuring spray deposition and drift. These findings contribute to the development of smart, data-driven spraying systems aimed at improving application precision, minimizing environmental impact, and supporting sustainable agricultural practices.