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Cited by 175

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Signalling drought in guard cells

Open access
Luan, S.·2002·Plant, Cell & Environment

Abstract

A number of environmental conditions including drought, low humidity, cold and salinity subject plants to osmotic stress. A rapid plant response to such stress conditions is stomatal closure to reduce water loss from plants. From an external stress signal to stomatal closure, many molecular components constitute a signal transduction network that couples the stimulus to the response. Numerous studies have been directed to resolving the framework and molecular details of stress signalling pathways in plants. In guard cells, studies focus on the regulation of ion channels by abscisic acid (ABA), a chemical messenger for osmotic stress. Calcium, protein kinases and phosphatases, and membrane trafficking components have been shown to play a role in ABA signalling process in guard cells. Studies also implicate ABA‐independent regulation of ion channels by osmotic stress. In particular, a direct osmosensing pathway for ion channel regulation in guard cells has been identified. These pathways form a complex signalling web that monitors water status in the environment and initiates responses in stomatal movements.

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Crossref · 10.1046/j.1365-3040.2002.00758.x

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Metadata

Authors
Luan, S.
Venue
Plant, Cell & Environment
Publisher
Wiley
Published
2002-02
Volume
25
Issue
2
Pages
229-237
ISSN
  • 0140-7791 (ISSN-L)
  • 1365-3040
OpenAlex
W2099050525
Cited by
175
References
1
FWCI
6.95
Type
journal article
Language
en
Open access
bronze

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Luan, S. (2002). Signalling drought in guard cells. Plant, Cell & Environment. https://doi.org/10.1046/j.1365-3040.2002.00758.x

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.