Generalized model of closed microecosystem «alga - micro-consumers».

IF 1.9 4区 生物学 Q2 BIOLOGY
V E Zalizniak, O A Zolotov, A I Chusovitina
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引用次数: 0

Abstract

Model of closed microecosystem "alga-micro-consumers" is proposed in this paper. Mathematical model is the Cauchy problem for system of nonlinear ordinary differential equations. To develop the model Liebig's law of the minimum is consistently used for both specific rate of biomass growth and specific death rate of alga and micro-consumers cells. To describe the specific rate of substrate utilization by alga and micro-consumer the Andrew model (substrate inhibition) is used. It is assumed that specific death rate of alga and micro-consumer cells increases with decreasing substrate concentration. It is also assumed that carbon and nitrogen are main biogenic elements, and in the system they are in the form of mineral substrate and biological substrate. To verify the proposed model experimental data for microecosystems «Chlorella vulgaris-Pseudomonas sp» and «Chlorella vulgaris-Pseudomonas sp-Mycobacterium rubrum» are used. These systems were studied in laboratory conditions, and concentrations of elements of microecosystems in stationary state were obtained. Parameters of functions describing specific rate of utilization of biogenic elements were derived from experimental data for growth kinetics of alga and bacteria. Concentration of the biomass in stationary state obtained with the use of the proposed model is in reasonable agreement with experimental data.

封闭微生态系统“藻类-微消费者”的广义模型。
提出了封闭微生态系统“藻类-微消费者”模型。数学模型是一类非线性常微分方程组的柯西问题。为了建立模型,李比希的最小值定律一直用于藻类和微消费者细胞的生物量比增长率和比死亡率。为了描述藻类和微消费者利用底物的具体速率,使用了安德鲁模型(底物抑制)。假设藻类和微消费细胞的比死亡率随底物浓度的降低而增加。同时认为碳和氮是主要的生物成因元素,在系统中以矿物基质和生物基质的形式存在。为了验证所提出的微生态系统模型的实验数据,使用了“普通小球藻-假单胞菌sp”和“普通小球藻-假单胞菌sp-红分枝杆菌”。在实验室条件下对这些系统进行了研究,得到了稳定状态下微生态系统中各元素的浓度。描述生物源元素利用率的函数参数来源于藻类和细菌生长动力学的实验数据。利用该模型得到的稳态生物量浓度与实验数据吻合较好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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