JOURNAL ARTICLE

Bringing home the carbon: photorespiratory CO2 recovery shows diverse efficiency in Brassicaceae.

  • Published In: Journal of Experimental Botany, 2023, v. 74, n. 21. P. 6399 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Walsh, Catherine A 3 of 3

Abstract

This article examines the efficiency and diversity of photorespiration, a metabolic pathway in plants that has traditionally been seen as wasteful. The authors focus on the Brassicaceae family, which includes important crop species, and investigate the presence of C3-C4 intermediates, plants that use a photorespiratory shuttle to concentrate carbon. They find that C3-C4 intermediacy is rare but present in some members of the Brassicaceae family, and they analyze the metabolic variation within this family compared to their closest C4 relative. The study provides insights into the evolution and optimization of photosynthetic pathways in different plant species. Additionally, the article discusses the potential of C3-C4 intermediates to enhance climate resilience in the face of climate change. The authors conducted a study on 28 species of Brassicaceae, a plant family without C4 relatives, and discovered significant diversity in their photosynthetic characteristics. They found that C3-C4 intermediates can efficiently reclaim CO2 and improve water use efficiency in low CO2 conditions, making them more adaptable to climate variability and abiotic stress compared to other photosynthetic types. The authors propose that these findings could be utilized to ensure food production and enhance agricultural sustainability in the future. [Extracted from the article]

Additional Information

  • Source:Journal of Experimental Botany. 2023/11, Vol. 74, Issue 21, p6399
  • Document Type:Article
  • Subject Area:Anatomy and Physiology
  • Publication Date:2023
  • ISSN:0022-0957
  • DOI:10.1093/jxb/erad371
  • Accession Number:173761181
  • Copyright Statement:Copyright of Journal of Experimental Botany is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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