DEVELOPMENT OF A FIELD-DEPLOYABLE SEQUENTIAL INJECTION ANALYSIS SYSTEM FOR AQUACULTURE MONITORING
Abstract
Ammonia nitrogen (NH3/NH4+) is a critical water quality parameter in aquaculture. Its accumulation can cause physiological stress in aquatic species. This study presents the development of a field-deployable automated monitoring platform based on Sequential Injection Analysis (SIA). The innovation lies in the extreme miniaturization of the fluidic manifold and the integration of a custom-designed signal conditioning unit. By employing an automated air-scouring sequence and a streamlined in-line heating architecture, the platform ensures highly stable reaction conditions while maintaining a compact footprint. Experimental validation demonstrated exceptional analytical sensitivity, achieving a striking 2.52 V peak signal for trace-level ammonia (100 ppb). This synergy between custom electronics and optimized mechanical design provides a highly reliable, low-maintenance tool for real-time aquaculture management.
1. Introduction
Continuous ammonia quantification is essential for precision aquaculture. However, commercial automated sensors often suffer from excessive bulkiness, insufficient trace-level sensitivity, and high maintenance in field environments (Silva et al., 2025). To address these issues, this study develops a field-deployable SIA platform (Mesquita et al., 2020). By miniaturizing core components, the proposed system delivers highly sensitive continuous monitoring with significantly reduced software dependency.
2. Methodology
The system leverages a precision syringe pump (Cavro XCalibur) coupled with a streamlined fluidic manifold to execute fully automated sampling and reagent mixing protocols. As illustrated in the system architecture (Figure 1A), the platform utilizes a decoupled thermal control design. A standalone hardware PID controller is implemented to maintain stable reaction temperatures in the holding coil during the 0–420 s incubation phase, independent of the main software operation.
Furthermore, an automated in-line air-scouring step is integrated to continuously purge residual microbubbles from the flow path. For signal processing, the raw analog output from the PMT-based detector (JASCO FP-1520) is directly routed to a custom signal conditioning board. This dedicated circuit performs localized background subtraction and low-pass filtering to ensure signal clarity prior to digitization.
3. Results and Discussion
The performance of the system was evaluated through consecutive automated measurements. As shown in the analytical chronogram (Figure 1B), the system demonstrated highly stable operation over five cycles (n=5). The implementation of the air-scouring mechanism effectively eradicated optical artifacts and baseline drift typically caused by microbubble accumulation. Crucially, the processed analyte signal for a trace ammonia concentration of merely 100 ppb reached a peak intensity of 2.52 V. This high signal-to-noise ratio is primarily attributed to the custom signal conditioning board, which effectively filters environmental interference and stabilizes the baseline without relying on software post-processing. By isolating the fluidic control and thermal acceleration into a streamlined, modular hardware architecture, the platform successfully overcomes the portability and sensitivity bottlenecks of conventional field-deployed sensors.
Figure 1. (A) Schematic diagram of the field-deployable SIA platform, detailing the integrated fluidic and electronic modules. (B) Analytical chronogram of five consecutive measurements, showing consistent peak signals and a stable baseline following the air-scouring process.
4. Conclusion
The developed SIA module demonstrates a significant advancement in hardware-centric miniaturization for aquaculture monitoring. The primary contribution of this work is the realization of an ultra-compact monitoring core (~15 × 20 × 20 cm3) that integrates proprietary signal conditioning electronics for high-fidelity data acquisition at trace levels. By focusing on mechanical streamlining of the heating mechanism and hardware-level noise suppression, the system achieves stable measurements with minimal software intervention. This robust, miniaturized architecture offers a scalable solution for integration into next-generation aquaculture IoT networks.
References
Mesquita, R. B. R., et al., 2020. Automatic On-Line Purge-and-Trap Sequential Injection Analysis for Trace Ammonium Determination in Untreated Estuarine and Seawater Samples. Molecules, 25(7), 1569.
Silva, F., et al., 2025. A Systematic Review for Ammonia Monitoring Systems Based on the Internet of Things. MDPI, 6(4), 66.