Strategies to reconstruct 3D Coffea arabica L. plant structure.

Q1 Multidisciplinary SpringerPlus Pub Date : 2016-12-05 eCollection Date: 2016-01-01 DOI:10.1186/s40064-016-3762-4
Fabio Takeshi Matsunaga, Jonas Barbosa Tosti, Armando Androcioli-Filho, Jacques Duílio Brancher, Evelyne Costes, Miroslava Rakocevic
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Abstract

Accurate model of structural elements is necessary to model the foliage and fruit distributions in cultivated plants, both of them being key parameters for yield prediction. However, the level of details in architectural data collection could vary, simplifying the data collection when plants get older and because of the high time cost required. In the present study, we aimed at reconstructing and analyzing plant structure, berry distributions and yield in Coffea arabica (Arabica coffee), by using both detailed or partial morphological information and probabilistic functions. Different datasets of coffee plant architectures were available with different levels of detail depending on the tree age. Three scales of decomposition-plant, axes and metamers were used reconstruct the plant architectures. CoffePlant3D, a software which integrates a series of mathematical, computational and statistical methods organized in three newly developed modules, AmostraCafe3D, VirtualCafe3D and Cafe3D, was developed to accurately reconstruct coffee plants in 3D, whatever the level of details available. The number of metamers of the 2nd order axes was shown to be linearly proportional to that of the orthotropic trunk, and the number of berries per metamer was modeled as a Gaussian function within a specific zone along the plagiotropic axes. This ratio of metamer emission rhythm between the orthotropic trunk and plagiotropic axes represents the pillar of botanical events in the C. arabica development and was central in our modeling approach, especially to reconstruct missing data. The methodology proposed for reconstructing coffee plants under the CoffePlant3D was satisfactorily validated across dataset available and could be performed for any other Arabica coffee variety.

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重建阿拉伯咖啡(Coffea arabica L.)植物三维结构的策略。
要建立栽培植物的叶片和果实分布模型,必须要有精确的结构元素模型,而叶片和果实分布都是产量预测的关键参数。然而,建筑数据收集的详细程度可能会有所不同,当植物变老时,数据收集就会简化,而且所需的时间成本也很高。在本研究中,我们旨在利用详细或部分形态信息以及概率函数,重建和分析阿拉比卡咖啡(Coffea arabica)的植株结构、浆果分布和产量。根据树龄的不同,咖啡植物结构数据集的详细程度也不同。使用了三种分解尺度--植株、轴和元胞来重建植物结构。CoffePlant3D 是一款集成了一系列数学、计算和统计方法的软件,分为三个新开发的模块:AmostraCafe3D、VirtualCafe3D 和 Cafe3D。结果表明,二阶轴的元胞数量与正交主干的元胞数量成线性比例,每个元胞的浆果数量被模拟为沿冥轴特定区域内的高斯函数。正交主干和垂轴之间的元粒发射节律比代表了阿拉伯金合欢树生长发育过程中植物学事件的支柱,也是我们建模方法的核心,特别是在重建缺失数据时。在 CoffePlant3D 中提出的重建咖啡植物的方法在现有数据集中得到了令人满意的验证,并可用于任何其他阿拉比卡咖啡品种。
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来源期刊
SpringerPlus
SpringerPlus MULTIDISCIPLINARY SCIENCES-
CiteScore
1.76
自引率
0.00%
发文量
0
期刊介绍: Cessation
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Erratum to: Coexistence of contralateral cluster headache and probable paroxysmal hemicrania: a case report Erratum to: Numerical method to compute acoustic scattering effect of a moving source. Erratum to: Associations between adherence, depressive symptoms and health-related quality of life in young adults with cystic fibrosis. Erratum to: Implication of Paris Agreement in the context of long-term climate mitigation goals. Adaptation Processes in Agriculture and Food Security: Insights from Evaluating Behavioral Changes in West Africa
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