Unverified paper record
Dynamics and Crosstalks of H 2 S and H 2 O 2 Signaling in Plant Abiotic Stress Response Deciphered by a Disposable SERS Sensing Patch.
ACS sensors · 27 Apr 2026 · 10.1021/acssensors.6c01065
Abstract
Abiotic stresses caused by climate change pose a serious threat to global crop productivity, making the early detection of plant stress responses crucial. Hydrogen sulfide (H 2 S) and hydrogen peroxide (H 2 O 2 ), as key signaling molecules, their dynamic synergistic effects are central to understanding the mechanisms of plant stress adaptation. However, real-time tracking of the dynamic changes of these molecules remains challenging. This study developed a wearable plasmonic nanoarray sensor integrated with metal-organic frameworks (MOFs), which cleverly combines the high sensitivity of surface-enhanced Raman scattering (SERS) with the gas enrichment capacity of the MOF, incorporates 2D plasmonic membrane assembly technology and 4-mercaptophenylboronic acid (4-MPBA) conjugation strategy, and successfully achieves real-time and synchronous detection of H 2 S and H 2 O 2 in plants. The 24 h dynamic monitoring results showed that under different stress conditions, H 2 S and H 2 O 2 in tomatoes and rice both had specific dynamic change rules, and there was a complex cross-regulation mechanism between them. By combining sensor data with partial least squares discriminant analysis (PLS-DA), the classification accuracy of stress types exceeds 95%. This non-destructive and highly sensitive detection system can provide real-time dynamic data of stress signals, bringing a breakthrough to the in-situ monitoring of plant physiological states.
Plant phenotyping relevance
植物内のストレスシグナルをリアルタイム測定するウェアラブルSERSセンサーの開発が研究の中心であり、植物の生理状態の表現型取得に直接結び付いている。
abstractThis study developed a wearable plasmonic nanoarray sensor integrated with metal-organic frameworks (MOFs)
abstractsuccessfully achieves real-time and synchronous detection of H 2 S and H 2 O 2 in plants
abstractThis non-destructive and highly sensitive detection system can provide real-time dynamic data of stress signals, bringing a breakthrough to the in-situ monitoring of plant physiological states.
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