Minimally Invasive Multimodal Flexible Sensors to Monitor Stem Growth Rate, Soil Water Content, and Soil pH

Smart agriculture, which integrates sensing, robotics, and AI technologies, offers a promising paradigm to optimize plant growth and resource efficiency. However, current biological monitoring systems are often bulky, invasive, or require multiple discrete devices, which limits their applicability during early stage plant growth. This study proposes a fully integrated, multimodal flexible sensor system capable of minimally invasive and continuous monitoring of key physiological and environmental parameters, i.e., stem growth rate, soil moisture, and soil pH. A kirigami-structured ultraflexible strain sensor is directly attached to the plant stem to monitor elongation with minimal mechanical interference, achieving the Young's modulus of 5.2 kPa and a strain range up to 340%. An impedance-based soil water sensor inserted into the soil exhibited a sensitivity of 8.1%/% within the 20-30% soil water content range. A polyaniline-based electrochemical pH sensor embedded in the soil showed a sensitivity of 49.2 mV/pH, determined from potentials immediately after irrigation events. Unlike conventional approaches, the proposed system realizes accurate, real-time monitoring even during the most sensitive stages of plant development. Notably, the system achieved continuous simultaneous monitoring of all parameters over 80 h under realistic conditions in a controlled growth chamber. The simultaneous acquisition of stem-based growth metrics and soil environmental data allows for a comprehensive understanding of plant physiology and supports precision agriculture. This work provides a scalable and minimally invasive platform for next-generation ecosystem-driven plant monitoring, thereby paving the way for data-informed, energy-efficient crop management strategies in sustainable agriculture.