利用真实的三维冠层模型计算野外光拦截的重要性。

IF 7.6 1区 农林科学 Q1 AGRONOMY
Shunfu Xiao, Shuaipeng Fei, Qing Li, Bingyu Zhang, Haochong Chen, Demin Xu, Zhibo Cai, Kaiyi Bi, Yan Guo, Baoguo Li, Zhen Chen, Yuntao Ma
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引用次数: 0

摘要

量化冠层截光量有助于深入了解植物间距、冠层结构和叶片朝向对辐射分布的影响。这对提高作物产量和改善产品质量至关重要。利用三维植物模型和光学模拟可以量化冠层的光拦截。然而,由于真实的三维冠层模型(RCMs)在野外很难获得,因此经常使用虚拟三维冠层模型(VCMs)来量化冠层的光拦截。本研究旨在比较vcm和RCM在光拦截方面的差异。采用先进的无人机交叉盘旋倾斜(CCO)路线和运动-多视点立体立体结构,在大面积上重建了逼真的三维玉米冠层模型(RCM)。然后在相应的RCM中心复制CCO构建的1、4和8个独立的真实植物,创建3种类型的vcm (VCM-1、VCM-4和VCM-8)。相对均方根误差(rRMSE)分别为20.22%、17.38%和15.48%,3个vcm的日单位面积截光量(DLI)与RCM存在明显偏差。尽管这种差异随着复制虚拟冠层的植物数量的增加而减小,但VCM-8和RCM的DLI的rRMSE仍然达到15.48%。研究还发现,rcm和vcm在早期(播种后48天[DAS])的光截获差异明显小于后期(播种后70天)。这项研究强调了在田间计算光拦截时使用RCM的重要性,特别是在植物生长后期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

The Importance of Using Realistic 3D Canopy Models to Calculate Light Interception in the Field.

The Importance of Using Realistic 3D Canopy Models to Calculate Light Interception in the Field.

The Importance of Using Realistic 3D Canopy Models to Calculate Light Interception in the Field.

The Importance of Using Realistic 3D Canopy Models to Calculate Light Interception in the Field.

Quantifying canopy light interception provides insight into the effects of plant spacing, canopy structure, and leaf orientation on radiation distribution. This is essential for increasing crop yield and improving product quality. Canopy light interception can be quantified using 3-dimensional (3D) plant models and optical simulations. However, virtual 3D canopy models (VCMs) have often been used to quantify canopy light interception because realistic 3D canopy models (RCMs) are difficult to obtain in the field. This study aims to compare the differences in light interception between VCMs and RCM. A realistic 3D maize canopy model (RCM) was reconstructed over a large area of the field using an advanced unmanned aerial vehicle cross-circling oblique (CCO) route and the structure from motion-multi-view stereo method. Three types of VCMs (VCM-1, VCM-4, and VCM-8) were then created by replicating 1, 4, and 8 individual realistic plants constructed by CCO in the center of the corresponding RCM. The daily light interception per unit area (DLI), as computed for the 3 VCMs, exhibited marked deviation from the RCM, as evinced by the relative root mean square error (rRMSE) values of 20.22%, 17.38%, and 15.48%, respectively. Although this difference decreased as the number of plants used to replicate the virtual canopy increased, rRMSE of DLI for VCM-8 and RCM still reached 15.48%. It was also found that the difference in light interception between RCMs and VCMs was substantially smaller in the early stage (48 days after sowing [DAS]) than in the late stage (70 DAS). This study highlights the importance of using RCM when calculating light interception in the field, especially in the later growth stages of plants.

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来源期刊
Plant Phenomics
Plant Phenomics Multiple-
CiteScore
8.60
自引率
9.20%
发文量
26
审稿时长
14 weeks
期刊介绍: Plant Phenomics is an Open Access journal published in affiliation with the State Key Laboratory of Crop Genetics & Germplasm Enhancement, Nanjing Agricultural University (NAU) and published by the American Association for the Advancement of Science (AAAS). Like all partners participating in the Science Partner Journal program, Plant Phenomics is editorially independent from the Science family of journals. The mission of Plant Phenomics is to publish novel research that will advance all aspects of plant phenotyping from the cell to the plant population levels using innovative combinations of sensor systems and data analytics. Plant Phenomics aims also to connect phenomics to other science domains, such as genomics, genetics, physiology, molecular biology, bioinformatics, statistics, mathematics, and computer sciences. Plant Phenomics should thus contribute to advance plant sciences and agriculture/forestry/horticulture by addressing key scientific challenges in the area of plant phenomics. The scope of the journal covers the latest technologies in plant phenotyping for data acquisition, data management, data interpretation, modeling, and their practical applications for crop cultivation, plant breeding, forestry, horticulture, ecology, and other plant-related domains.
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