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首页> 外文期刊>Bioprocess and Biosystems Engineering >Modeling hairy root tissue growth in in vitro environments using an agent-based, structured growth model
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Modeling hairy root tissue growth in in vitro environments using an agent-based, structured growth model

机译:使用基于代理的结构化生长模型在体外环境中对毛状根组织生长进行建模

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摘要

An agent-based model for simulating the in vitro growth of Beta vulgaris hairy root cultures is described. The model fitting is based on experimental results and can be used as a virtual experimentator for root networks. It is implemented in the JAVA language and is designed to be easily modified to describe the growth of diverse biological root networks. The basic principles of the model are outlined, with descriptions of all of the relevant algorithms using the ODD protocol, and a case study is presented in which it is used to simulate the development of hairy root cultures of beetroot (Beta vulgaris) in a Petri dish. The model can predict various properties of the developing network, including the total root length, branching point distribution, segment distribution and secondary metabolite accumulation. It thus provides valuable information that can be used when optimizing cultivation parameters (e.g., medium composition) and the cultivation environment (e.g., the cultivation temperature) as well as how constructional parameters change the morphology of the root network. An image recognition solution was used to acquire experimental data that were used when fitting the model and to evaluate the agreement between the simulated results and practical experiments. Overall, the case study simulation closely reproduced experimental results for the cultures grown under equivalent conditions to those assumed in the simulation. A 3D-visualization solution was created to display the simulated results relating to the state of the root network and its environment (e.g., oxygen and nutrient levels).
机译:描述了一种基于代理的模型,用于模拟寻常型Beta毛状根培养物的体外生长。模型拟合基于实验结果,可以用作根网络的虚拟实验者。它是用JAVA语言实现的,旨在易于修改以描述各种生物根网络的增长。概述了该模型的基本原理,并使用ODD协议对所有相关算法进行了描述,并提供了一个案例研究,该案例可用于模拟培养皿中甜菜根(Beta vulgaris)毛状根培养的发育碟。该模型可以预测正在发育的网络的各种特性,包括总根长,分支点分布,片段分布和次生代谢产物积累。因此,它提供了有价值的信息,可在优化栽培参数(例如培养基组成)和栽培环境(例如栽培温度)以及构造参数如何改变根网络的形态时使用。图像识别解决方案用于获取拟合模型时使用的实验数据,并评估模拟结果与实际实验之间的一致性。总体而言,案例研究模拟重现了在与模拟假设相同的条件下生长的培养物的实验结果。创建了3D可视化解决方案以显示与根网络状态及其环境有关的模拟结果(例如,氧气和营养水平)。

著录项

  • 来源
    《Bioprocess and Biosystems Engineering》 |2014年第6期|1173-1184|共12页
  • 作者单位

    Mechanical Science and Engineering, Institute of Food Technology and Bioprocess Engineering, Technische Universitaet Dresden, Dresden, Germany;

    Institute of Scientific Computing, Technische Universitaet Dresden, Dresden, Germany;

    Institute of Scientific Computing, Technische Universitaet Dresden, Dresden, Germany;

    Mechanical Science and Engineering, Institute of Food Technology and Bioprocess Engineering, Technische Universitaet Dresden, Dresden, Germany;

    Mechanical Science and Engineering, Institute of Food Technology and Bioprocess Engineering, Technische Universitaet Dresden, Dresden, Germany;

    Mechanical Science and Engineering, Institute of Food Technology and Bioprocess Engineering, Technische Universitaet Dresden, Dresden, Germany;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Hairy roots; Beta vulgaris; Growth modeling; Plant cell tissue; Agent-based model;

    机译:多毛的根;甜菜成长模型;植物细胞组织;基于代理的模型;

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