Screen-printed graphite electrode on polyvinyl chloride and parchment strips integrated with genetic programming for in situ nitrate sensing of aquaponic pond water

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@Article{CONCEPCION:2023:inpa,

• author = "Ronnie Concepcion and Bernardo Duarte and Maria {Gemel Palconit} and Jonah Jahara Baun and Argel Bandala and Ryan {Rhay Vicerra} and Elmer Dadios",
• title = "Screen-printed graphite electrode on polyvinyl chloride and parchment strips integrated with genetic programming for in situ nitrate sensing of aquaponic pond water",
• journal = "Information Processing in Agriculture",
• year = "2023",
• ISSN = "2214-3173",
• DOI = "doi:10.1016/j.inpa.2023.02.002",
• URL = "https://www.sciencedirect.com/science/article/pii/S2214317323000124",
• keywords = "genetic algorithms, genetic programming, aquaponic water quality, electrochemical technology, graphite electrode, nitrate sensor, precision agriculture, printed electronics, scanning electron microscopy, screen-printed electrode, voltammetry",
• abstract = "Nitrate is the primary water-soluble macronutrient essential for plant growth that is converted from excess fish feeds, fish effluents, and degrading biomaterials on the aquaponic pond floor, and when aquacultural malpractices occur, large amounts of it retain in the water system causing increase rate in eutrophication and toxifies fish and aquaculture plants. Recent nitrate sensor prototypes still require performing the additional steps of water sample deionization and dilution and were constructed with expensive materials. In response to the challenge of sensor enhancement and aquaponic water quality monitoring, this study developed sensitive, repeatable, and reproducible screen-printed graphite electrodes on polyvinyl chloride and parchment paper substrates with silver as electrode material and 60:40 graphite powder:nail polish formulated conductive ink for electrical traces, integrated with 9-gene genetic expression model as a function of peak anodic current and electrochemical test time for nitrate concentration prediction that is embedded into low-power Arduino ESP32 for in situ nitrate sensing in aquaponic pond water. Five SPE electrical traces were designed on the two types of substrates. Scanning electron microscopy with energy dispersive X-ray confirmed the electrode surface morphology. Electrochemical cyclic voltammetry using 10 to 100 mg/L KNO3 and water from three-depth regions of the actual pond established the electrochemical test time (10.5 s) and electrode potential (0.135 V) protocol necessary to produce peak current that corresponds to the strength of nitrate ions during redox. The findings from in situ testing revealed that the proposed sensors have strong linear predictions (R2=0.968 MSE=1.659 for nSPEv and R2=0.966 MSE=4.697 for nSPEp) in the range of 10 to 100 mg/L and best detection limit of 3.15 ?g/L, which are comparable to other sensors of more complex construction. The developed three-electrode electrochemical nitrate sensor confirms that it is reliable for both biosensing in controlled solutions and in situ aquaponic pond water systems",

}

Genetic Programming entries for Ronnie S Concepcion II Bernardo Duarte Maria Gemel B Palconit Jonah Jahara Garcia Baun Argel A Bandala Ryan Rhay P Vicerra Elmer Jose P Dadios

Citations