JOURNAL ARTICLE
Molecular, hormonal, and metabolic mechanisms of fruit set, the ovary-to-fruit transition, in horticultural crops.
Published In: Journal of Experimental Botany, 2023, v. 74, n. 20. P. 6254 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Ezura, Kentaro; Nomura, Yukako; Ariizumi, Tohru 3 of 3
Abstract
The article focuses on the molecular, hormonal, cellular, and metabolic mechanisms underlying fruit set in tomato (Solanum lycopersicum), the process by which the ovary develops into fruit, critically influencing fruit yield. Fruit set is primarily regulated by the phytohormones auxin and gibberellin (GA), with auxin biosynthesis in fertilized ovules triggering signaling cascades that promote cell division, followed by GA-mediated cell expansion and activation of central carbon metabolism to supply energy and biomass for rapid fruit growth. Negative regulators such as SlIAA9 and SlDELLA/PROCERA repress auxin and GA signaling before fertilization and are degraded upon pollination, enabling fruit development; ethylene and jasmonic acid also modulate fruit set by interacting with these hormonal pathways. Additionally, transcription factors including MADS-box genes and epigenetic modifications contribute to the regulation of fruit set, while active sucrose metabolism and transport support the energetic demands of early fruit growth. Understanding these integrated regulatory networks in tomato provides insights potentially applicable to improving fruit yield stability in other crop species.
Additional Information
- Source:Journal of Experimental Botany. 2023/10, Vol. 74, Issue 20, p6254
- Document Type:Article
- Subject Area:Agriculture and Agribusiness
- Publication Date:2023
- ISSN:0022-0957
- DOI:10.1093/jxb/erad214
- Accession Number:173339256
- 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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