3D-Printed Graphene Electrodes Applied in an Impedimetric Electronic Tongue for Soil Analysis

• Main Authors: Tatiana Americo da Silva, Maria Luisa Braunger, Marcos Antonio Neris Coutinho, Lucas Rios do Amaral, Varlei Rodrigues, Antonio Riul
• Format: Article
• Language: English
• Published: MDPI AG 2019-10-01
• Series: Chemosensors
• Subjects: layer-by-layer films; e-tongue; soil analysis; 3d printing
• Online Access: https://www.mdpi.com/2227-9040/7/4/50

The increasing world population leads to the growing demand for food production without expanding cultivation areas. In this sense, precision agriculture optimizes the production and input usage by employing sensors to locally monitor plant nutrient within agricultural fields. Here, we have used an electronic tongue sensing device based on impedance spectroscopy to recognize distinct soil samples (sandy and clayey) enriched with macronutrients. The e-tongue setup consisted of an array of four sensing units formed by layer-by-layer (LbL) films deposited onto 3D-printed graphene-based interdigitated electrodes (IDEs). The IDEs were fabricated in 20 min using the fused deposition modeling process and commercial polylactic acid-based graphene filaments. The e-tongue comprised one bare and three IDEs functionalized with poly(diallyldimethylammonium chloride) solution/copper phthalocyanine-3,4′,4″,4‴-tetrasulfonic acid tetrasodium salt (PDDA/CuTsPc), PDDA/montmorillonite clay (MMt-K), and PDDA/poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS) LbL films. Control samples of sandy and clayey soils were enriched with different concentrations of nitrogen (N), phosphorus (P), and potassium (K) macronutrients. Sixteen soil samples were simply diluted in water and measured using electrical impedance spectroscopy, with data analyzed by principal component analysis. All soil samples were easily distinguished without pre-treatment, indicating the suitability of 3D-printed electrodes in e-tongue analysis to distinguish the chemical fertility of soil samples. Our results encourage further investigations into the development of new tools to support precision agriculture.