探索新陈代谢昼长测量系统:对光周期生长的影响。

IF 9.4 1区 生物学 Q1 Agricultural and Biological Sciences New Phytologist Pub Date : 2024-11-15 DOI:10.1111/nph.20275
Man-Wah Li, Joshua M Gendron
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引用次数: 0

摘要

光周期是一种环境信号,在一年中会发生可预测的变化。因此,可用于光合作用的日照时间以及植物积累碳资源的能力也会在一年中波动。为了适应光周期的这些变化,新陈代谢昼长测量(MDLM)系统测量的是光合周期而不是绝对光周期,并将其转化为与光周期生长相关的季节性基因表达变化。在本篇 "坦斯利透视"(Tansley Insight)中,我们简要总结了目前对 MDLM 系统的了解,并强调了我们知识中的空白。鉴于该系统在季节性生长中的关键作用,了解 MDLM 系统对于提高植物对不同光周期的适应性和优化农业生产至关重要。
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Exploring the metabolic daylength measurement system: implications for photoperiodic growth.

Photoperiod is an environmental signal that varies predictably across the year. Therefore, the duration of sunlight available for photosynthesis and in turn the ability of plants to accumulate carbon resources also fluctuates across the year. To adapt to these variations in photoperiod, the metabolic daylength measurement (MDLM) system measures the photosynthetic period rather than the absolute photoperiod, translating it into seasonal gene expression changes linked to photoperiodic growth. In this Tansley Insight, we briefly summarize the current understanding of the MDLM system and highlight gaps in our knowledge. Given the system's critical role in seasonal growth, understanding the MDLM system is essential for enhancing plant adaptation to different photoperiods and optimizing agricultural production.

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来源期刊
New Phytologist
New Phytologist PLANT SCIENCES-
CiteScore
17.60
自引率
5.30%
发文量
728
审稿时长
1 months
期刊介绍: New Phytologist is a leading publication that showcases exceptional and groundbreaking research in plant science and its practical applications. With a focus on five distinct sections - Physiology & Development, Environment, Interaction, Evolution, and Transformative Plant Biotechnology - the journal covers a wide array of topics ranging from cellular processes to the impact of global environmental changes. We encourage the use of interdisciplinary approaches, and our content is structured to reflect this. Our journal acknowledges the diverse techniques employed in plant science, including molecular and cell biology, functional genomics, modeling, and system-based approaches, across various subfields.
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