Decoding plant volatile stress signals across scales: from molecular responses to ecosystem dynamics

• 全文链接

跨尺度解码植物挥发物胁迫信号：从分子响应到生态系统动态

关键词：

来源：

Frontiers in Plant Science 期刊

全文链接：

//agri.nais.net.cn/topic/downloadFile/71092f79-04d9-40f3-8e0d-05d307e42f28

来源地址：

https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2026.1815183/full

资源所属：

茶学研究专题

类型：

学术文献

语种：

英语

原文发布日期：

2026-06-02

摘要：

Plant volatile organic compounds (VOCs) represent one of the most dynamic and integrative biochemical signaling systems linking molecular plant stress responses to ecosystem-level processes. This review provides an integrative cross-scale framework for understanding the biochemical pathways, regulatory networks, ecological functions, and technological applications of stress-induced volatile emissions. At the molecular and cellular levels, VOC emissions are regulated through complex enzymatic and hormonal pathways involving jasmonates, salicylates, ethylene, and abscisic acid, enabling plants to respond rapidly to abiotic and biotic stressors such as drought, herbivory, temperature extremes, salinity, and atmospheric pollution. These volatile signals extend beyond individual plants, functioning as mediators of plant–plant communication, plant–microbe interactions, and multi-trophic ecological networks that shape community dynamics and ecosystem resilience. Recent technological advancements, including mass spectrometry platforms, remote sensing systems, biosensors, and artificial intelligence–driven analytical frameworks, have transformed the ability to detect, interpret, and predict stress-induced VOC emissions in real time. Integrating these technologies with multi-omics datasets and digital twin modeling enables the development of predictive monitoring systems capable of scaling plant stress detection from agricultural fields to regional ecosystems. Despite these advances, significant challenges remain, including variability in emission profiles across species and environments, atmospheric transformation of volatile signals, methodological inconsistencies, and limitations in large-scale monitoring infrastructure. Future research should focus on establishing global networks for monitoring plant volatiles, standardized measurement protocols, and integrated biosensing infrastructures that can link plant stress signals to Earth-system observations. Decoding plant volatile stress signaling across scales offers a transformative pathway to advance climate-resilient agriculture, biodiversity conservation, and predictive environmental intelligence systems that support adaptive ecosystem management in an era of accelerating environmental change.