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Cited by 294

The DOI matches its Crossref record; 120 of the 120 references it cites were found in a registry or an index.

Abiotic stress responses in plant roots: a proteomics perspective

Open access
Ghosh, Dipanjana, Xu, Jian·2014·Frontiers in Plant Science

Abstract

Abiotic stress conditions adversely affect plant growth, resulting in significant decline in crop productivity. To mitigate and recover from the damaging effects of such adverse environmental conditions, plants have evolved various adaptive strategies at cellular and metabolic levels. Most of these strategies involve dynamic changes in protein abundance that can be best explored through proteomics. This review summarizes comparative proteomic studies conducted with roots of various plant species subjected to different abiotic stresses especially drought, salinity, flood, and cold. The main purpose of this article is to highlight and classify the protein level changes in abiotic stress response pathways specifically in plant roots. Shared as well as stressor-specific proteome signatures and adaptive mechanism(s) are simultaneously described. Such a comprehensive account will facilitate the design of genetic engineering strategies that enable the development of broad-spectrum abiotic stress-tolerant crops.

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Metadata

Authors
Ghosh, D., & Xu, J.
Venue
Frontiers in Plant Science
Published
2014
Volume
5
Pages
6-6
ISSN
1664-462X (ISSN-L)
OpenAlex
W2161897097
Cited by
294
References
120
FWCI
26.31
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Abiotic stress responses in plant roots: a proteomics perspective. https://app.cochat.ai/papers/10.3389/fpls.2014.00006
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Ghosh, D., & Xu, J. (2014). Abiotic stress responses in plant roots: a proteomics perspective. Frontiers in Plant Science. https://doi.org/10.3389/fpls.2014.00006

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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.