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高光谱近地感知在叶片和冠层尺度估算光合能力中的应用。

Hyperspectral Proximal Sensing for Estimating Photosynthetic Capacities at Leaf and Canopy Scales.

机构信息

Center for Advanced Agriculture and Sustainability, Harrisburg University, Harrisburg, PA, USA.

Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.

出版信息

Methods Mol Biol. 2024;2790:355-372. doi: 10.1007/978-1-0716-3790-6_18.

Abstract

Agronomists, plant breeders, and plant biologists have been promoting the need to develop high-throughput methods to measure plant traits of interest for decades. Measuring these plant traits or phenotypes is often a bottleneck since skilled personnel, resources, and ample time are required. Additionally, plant phenotypic traits from only a select number of breeding lines or varieties can be quantified because the "gold standard" measurement of a desired trait cannot be completed in a timely manner. As such, numerous approaches have been developed and implemented to better understand the biology and production of crops and ecosystems. In this chapter, we explain one of the recent approaches leveraging hyperspectral measurements to estimate different aspects of photosynthesis. Notably, we outline the use of hyperspectral radiometer and imaging to rapidly estimate two of the rate-limiting steps of photosynthesis: the maximum rate of the carboxylation of Rubisco (V) and the maximum rate of electron transfer or regeneration of RuBP (J).

摘要

几十年来,农学家、植物育种家和植物生物学家一直在提倡开发高通量方法来测量感兴趣的植物性状。测量这些植物性状或表型通常是一个瓶颈,因为需要熟练的人员、资源和充足的时间。此外,由于无法及时完成所需性状的“金标准”测量,因此只能对少数几个选育系或品种的植物表型性状进行量化。因此,已经开发并实施了许多方法来更好地了解作物和生态系统的生物学和生产。在本章中,我们解释了利用高光谱测量来估计光合作用不同方面的最新方法之一。值得注意的是,我们概述了使用高光谱辐射计和成像来快速估计光合作用的两个限速步骤:Rubisco(V)羧化的最大速率和 RuBP(J)的电子传递或再生成的最大速率。

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