Plant Stress Detection via Molecular Communication: Modeling BVOC-Based Inter-Plant Signaling for Agricultural Monitoring.

Abstract

In the plant kingdom, stress can significantly impact physiological and metabolic processes, leading to growth inhibition, developmental abnormalities, and even mortality. Current detection methods primarily focus on changes in gene expression or observable disease symptoms. However, these approaches are often resource-intensive, costly, and procedurally complex. To overcome these challenges, this study introduces an innovative molecular communication framework for plant stress monitoring. In this framework, plants that release biogenic volatile organic compounds serve as transmitters, receiving plants act as receivers, and the air serves as the propagation channel. The primary objective is to develop a real-time stress detection method by modulating stress types into distinct profiles of biogenic volatile organic compounds. These profiles are transmitted as chemical signals and are demodulated at the receiver. We analyzed the effects of distance, wind speed, and other factors on compound dispersion in the channel, validating the system through simulations and a molecular communication testbed. This research provides an innovative technical approach for real-time plant stress monitoring while establishing a theoretical foundation for enhancing crop management efficiency and advancing precision agriculture.

Plant phenotyping relevance

植物ストレス状態をBVOCシグナルから検出する技術を中心に開発し、シミュレーションとテストベッドで検証しているため、単なる分子分析ではなく植物表現型状態の測定法に該当する。

Code and data availability

The paper describes MATLAB simulations and a pigment-based molecular communication testbed, but contains no public phenotype/trait dataset, no deposited images or sensor data, and no author code release. No data or code availability statement with a public URL appears in the supplied blocks; the only URLs are the ORCID

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