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An In Situ Gelled PCA-Na/Gelatin Hydrogel Plant Wearable Sensor Patch Based on Synergistic Enhancement Strategy for
Jie Wei1, Mengjie Wang1, Hao Zhang1
1School of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, P. R. China.
None:
Plant wearable sensors have broad application potential in crop physiological monitoring, early warning of pests and diseases, and real-time detection of pesticide residues. However, challenges such as insufficient accuracy, poor mechanical adaptability, and inadequate stability still exist. To solve this problem, a sodium l-pyroglutamate (PCA-Na) modified gelatin hydrogel was constructed for the preparation of wearable sensor patch. The prepared hydrogel sensor demonstrates integrated advantages of enhanced mechanical strength, high ionic conductivity, good surface adhesion, and low detection limit (LOD). Based on the temperature dependent phase transition characteristics of gelatin, it could undergo in situ gelatinization on the plant surface, effectively reducing the impact of external environmental interference. More importantly, the electrostatic attraction between gelatin and PCA-Na could promote ionic cross-linking and significantly enhance the mechanical properties, water retention, and long-term stability of hydrogels. Meanwhile, the high mobility of Na+ in the network of gelatin hydrogel further enhanced the ionic conductivity of working electrode. The sensor exhibited a wide linear range of 0.01 ng/mL to 2 μg/mL for atrazine (ATZ) and a low limit of detection (LOD) of 0.003 ng/mL, enabling sensitive monitoring of trace physiological signals in plants. Therefore, a synergistic enhancement strategy was proposed, including ion cross-linking to enhance mechanical properties, hydrogen bonding networks to maintain water retention stability, and free ion enhanced conductivity. This work established a proof-of-concept for the modification of hydrogel and integration of plant wearable sensor that could provide the innovative inspiration for the development of efficient detection methods of modern agriculture.
