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Cited by 277

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Root decisions

Open access
HODGE, ANGELA·2009·Plant, Cell & Environment

Abstract

Root systems have recognizable developmental plans when grown in solution or agar; however, these plans often must be modified to cope with the prevailing conditions in the soil environment such as the avoidance of obstacles and the exploitation of nutrient‐rich patches or water zones. The modular structure of roots enables them to respond to their environment, and roots are very adaptive at modifying growth throughout the root system to concentrate their efforts in the areas that are the most profitable. Roots also form associations with microorganisms as a strategy to enhance resource capture. However, while the responses of roots in nutrient patches are well‐recognized, overall ‘rules of response’ and variation in strategy among plant species that can be applied in a number of different environments are still lacking. Finally, there is increasing evidence that root–root interactions are much more sophisticated than previously thought, and the evidence for roots to identify self from non‐self roots will be briefly discussed.

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Crossref · 10.1111/j.1365-3040.2008.01891.x

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Citations

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Metadata

Authors
HODGE, A.
Venue
Plant, Cell & Environment
Publisher
Wiley
Published
2009-05-07
Volume
32
Issue
6
Pages
628-640
ISSN
  • 0140-7791 (ISSN-L)
  • 1365-3040
OpenAlex
W4210340613
Cited by
277
References
2
FWCI
14.27
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Root decisions. https://app.cochat.ai/papers/10.1111/j.1365-3040.2008.01891.x
The paper
HODGE, A. (2009). Root decisions. Plant, Cell & Environment. https://doi.org/10.1111/j.1365-3040.2008.01891.x

Data sources

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.