Literature DB >> 27374843

Efficiency of chlorophyll in gross primary productivity: A proof of concept and application in crops.

Anatoly A Gitelson1, Yi Peng2, Andrés Viña3, Timothy Arkebauer4, James S Schepers4.   

Abstract

One of the main factors affecting vegetation productivity is absorbed light, which is largely governed by chlorophyll. In this paper, we introduce the concept of chlorophyll efficiency, representing the amount of gross primary production per unit of canopy chlorophyll content (Chl) and incident PAR. We analyzed chlorophyll efficiency in two contrasting crops (soybean and maize). Given that they have different photosynthetic pathways (C3 vs. C4), leaf structures (dicot vs. monocot) and canopy architectures (a heliotrophic leaf angle distribution vs. a spherical leaf angle distribution), they cover a large spectrum of biophysical conditions. Our results show that chlorophyll efficiency in primary productivity is highly variable and responds to various physiological and phenological conditions, and water availability. Since Chl is accessible through non-destructive, remotely sensed techniques, the use of chlorophyll efficiency for modeling and monitoring plant optimization patterns is practical at different scales (e.g., leaf, canopy) and under widely-varying environmental conditions. Through this analysis, we directly related a functional characteristic, gross primary production with a structural characteristic, canopy chlorophyll content. Understanding the efficiency of the structural characteristic is of great interest as it allows explaining functional components of the plant system.
Copyright © 2016 Elsevier GmbH. All rights reserved.

Entities:  

Keywords:  Crops; Maize; PAR; Phenology; Primary production; Soybean; Water status

Mesh:

Substances:

Year:  2016        PMID: 27374843     DOI: 10.1016/j.jplph.2016.05.019

Source DB:  PubMed          Journal:  J Plant Physiol        ISSN: 0176-1617            Impact factor:   3.549


  3 in total

Review 1.  Utilization of Spectral Indices for High-Throughput Phenotyping.

Authors:  Rupesh Tayade; Jungbeom Yoon; Liny Lay; Abdul Latif Khan; Youngnam Yoon; Yoonha Kim
Journal:  Plants (Basel)       Date:  2022-06-28

2.  Optimal Spectral Wavelengths for Discriminating Orchard Species Using Multivariate Statistical Techniques.

Authors:  Mozhgan Abbasi; Jochem Verrelst; Mohsen Mirzaei; Safar Marofi; Hamid Reza Riyahi Bakhtíari
Journal:  Remote Sens (Basel)       Date:  2019-12-23       Impact factor: 5.349

3.  Estimating photosynthetic capacity from leaf reflectance and Chl fluorescence by coupling radiative transfer to a model for photosynthesis.

Authors:  Nastassia Vilfan; Christiaan van der Tol; Wouter Verhoef
Journal:  New Phytol       Date:  2019-04-13       Impact factor: 10.151

  3 in total

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