On-line measurement of biomass using colloid dielectric probe and open-ended cell. Determination of the aggregation threshold

M. Merabet
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Abstract

This paper presents a new approach to assess the biomass concentration of bacteria in a culture medium. It is based on the use of the colloid inductive permittivity probe, which is not affected by the electrode polarization, complemented by the traditional open-ended coaxial line measuring method. The method probes the interactions between the membranes of the cells and the applied electric fields in the RF and the Microwave frequency ranges. It allows the characterization of each type of cells with a specific relaxation process. The specific relaxation frequency is used as a fingerprint of the cell strain, while the relaxation amplitude is related to its concentration. By using appropriate and complementary de-convolution techniques, it is possible to identify reliably the elementary relaxation processes. Specifically, the frequency-dependent dielectric responses of Lactobacilli in DMEM are investigated in the [75 KHz–30 MHz] and in the [130 MHz–20 GHz] ranges. The method is tested against biological standard methods, and used successfully to predict concentration of Lactobacilli in adverse conditions. Moreover, because of the direct measurement over large concentration ranges, the concentration threshold of the bacteria aggregation can be precisely identified from the behavior of the amplitude of the specific medium-frequency relaxation process, characterized by a transition from a linear evolution to a second straight line with a different slope. The method can be easily adapted to the on-line monitoring of the growth of biological cells and to the control of the fermentation processes.
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利用胶体介电探针和开放式电池在线测量生物量。聚合阈值的确定
本文提出了一种评估培养基中细菌生物量浓度的新方法。它以不受电极极化影响的胶体电感介电常数探头为基础,辅以传统的开放式同轴线测量方法。该方法在射频和微波频率范围内探测细胞膜与外加电场之间的相互作用。它可以用特定的松弛过程来描述每种类型的细胞。特定的弛豫频率作为细胞株的指纹,而弛豫振幅与其浓度有关。通过使用适当的和互补的反卷积技术,可以可靠地识别基本松弛过程。具体来说,在[75 KHz-30 MHz]和[130 MHz - 20 GHz]范围内,研究了乳酸菌在DMEM中的频率相关介电响应。该方法与生物标准方法进行了对比试验,并成功地用于预测不良条件下乳酸菌的浓度。此外,由于在大浓度范围内的直接测量,细菌聚集的浓度阈值可以从特定中频弛豫过程的振幅行为精确地识别出来,其特征是从线性演变到具有不同斜率的第二条直线。该方法易于适应生物细胞生长的在线监测和发酵过程的控制。
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