Research Article | Open Access
Volume 2024 |Article ID 0217 | https://doi.org/10.34133/plantphenomics.0217

Maximizing the Radiation Use Efficiency by Matching the Leaf Area and Leaf Nitrogen Vertical Distributions in a Maize Canopy: A Simulation Study

Baiyan Wang,1,2,4 Shenghao Gu,1,4 Junhao Wang,1,3,4 Bo Chen,1 Weiliang Wen,1 Xinyu Guo ,1 and Chunjiang Zhao 1

1Beijing Key Lab of Digital Plant, Information Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
2Nanjing Agricultural University, MSU Institute, Nanjing 210095, China
3China Agricultural University, College of Resources and Environmental Sciences, Beijing 100193, China
4These authors contributed equally to this work

Received 
30 Dec 2023
Accepted 
19 Jun 2024
Published
29 Jul 2024

Abstract

The radiation use efficiency (RUE) is one of the most important functional traits determining crop productivity. The coordination of the vertical distribution of light and leaf nitrogen has been proven to be effective in boosting the RUE from both experimental and computational evidence. However, previous simulation studies have primarily assumed that the leaf area is uniformly distributed along the canopy depth, rarely considering the optimization of the leaf area distribution, especially for C4 crops. The present study hypothesizes that the RUE may be maximized by matching the leaf area and leaf nitrogen vertical distributions in the canopy. To test this hypothesis, various virtual maize canopies were generated by combining the leaf inclination angle, vertical leaf area distribution, and vertical leaf nitrogen distribution and were further evaluated by an improved multilayer canopy photosynthesis model. We found that a greater fraction of leaf nitrogen is preferentially allocated to canopy layers with greater leaf areas to maximize the RUE. The coordination of light and nitrogen emerged as a property from the simulations to maximize the RUE in most scenarios, particularly in dense canopies. This study not only facilitates explicit and precise profiling of ideotypes for maximizing the RUE but also represents a primary step toward high-throughput phenotyping and screening of the RUE for massive numbers of inbred lines and cultivars.

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