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Cited by 305

The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.

Optogenetic manipulation of stomatal kinetics improves carbon assimilation, water use, and growth

Open access
Papanatsiou, M., Petersen, J., Henderson, L., Wang, Y., Christie, J. M., Blatt, M. R.·2019·Science

Abstract

Speeding up stomatal responses: A plant's cellular metabolism rapidly adjusts to changes in light conditions, but its stomata—pores that allow gas exchange in leaves—are slower to respond. Because of the lagging response, photosynthesis is less efficient, and excess water is lost through the open pores. Papanatsiou et al. introduced a blue light–responsive ion channel into stomata of the small mustard plant Arabidopsis. The channel increased the rate of stomata opening and closing in response to light. The engineered plants produced more biomass, especially in the fluctuating light conditions typical of outdoor growth. Science , this issue p. 1456

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Crossref · 10.1126/science.aaw0046

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Metadata

Authors
Papanatsiou, M., Petersen, J., Henderson, L., Wang, Y., Christie, J. M., & Blatt, M. R.
Venue
Science
Published
2019-03-29
Volume
363
Issue
6434
Pages
1456-1459
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2924443446
Cited by
305
References
34
FWCI
10.96
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Optogenetic manipulation of stomatal kinetics improves carbon assimilation, water use, and growth. https://app.cochat.ai/papers/10.1126/science.aaw0046
The paper
Papanatsiou, M., Petersen, J., Henderson, L., Wang, Y., Christie, J. M., & Blatt, M. R. (2019). Optogenetic manipulation of stomatal kinetics improves carbon assimilation, water use, and growth. Science. https://doi.org/10.1126/science.aaw0046

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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.