Wearable device for in-situ plant sap analysis: Electrochemical lateral flow (eLF) for stress monitoring in living plants.

Abstract

Smart agriculture and environmental monitoring claim innovative wearable sensing technologies suitable for real-time, in-situ biochemical analysis for non-specialized users in plants. Current strategies measure physical parameters, ions or hormones by amperometry or potentiometry. Among these, plant hormones serve as stress biomarkers due to their role in stress response mechanisms. While electrocatalysis has been explored for their detection, early-stage stress monitoring at low concentrations demands higher selectivity and specificity. Therefore, new strategies integrating biorecognition elements, such as antibodies, with autonomous sample collection and bioassay performance are required. In this regard, this work proposes a novel wearable immunosensor device based on an electrochemical lateral flow assay (eLF) that includes an autonomous microsampling technology for minimally invasive in-situ sap extraction and abscisic acid (ABA) detection. This sap device collects, processes and analyzes plant sap with low sample volume (<10 μL) and short assay time (9min) using immunosensing for the first time in ABA wearable detection. Validation in drought-stressed cucumber plants demonstrated 78 % sensitivity and 71 % specificity in detecting subtle water stress with 77 % accuracy. These findings highlight the potential of this plant-wearable biosensor for early stress detection and its versatility to be adapted for the detection of other relevant molecules (proteins or DNA), key for smart agriculture and environmental monitoring.

Plant phenotyping relevance

植物体内のABAを低侵襲に採取・測定するウェアラブル電気化学センサーを開発し、乾燥ストレス検出性能を検証しており、植物状態の取得方法が中心である。

Code and data availability

The paper reports a wearable electrochemical lateral flow biosensor for ABA detection in cucumber sap, but no public phenotype datasets, images, code, models, or supplements are provided. The data availability statement explicitly states the data is confidential, and no repository or URL for paper-specific assets is给定.

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