Departamento de Biotecnología y Bioingeniería, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, 07360, Ciudad de México, Mexico.
Environmental Biotechnology and Renewable Energies Group, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Av. Instituto Politécnico Nacional 2508, Col. San Pedro Zacatenco, 07360, Ciudad de México, Mexico.
Bioprocess Biosyst Eng. 2018 Oct;41(10):1471-1484. doi: 10.1007/s00449-018-1975-3. Epub 2018 Jul 3.
On bioprocess engineering, experimental measurements are always a costly part of the modeling effort; therefore, there is a constant need to develop cheaper, simpler, and more efficient methodologies to exploit the information available. The aim of the present work was to develop a soft sensor with the capacity to perform reliable substrate predictions and control in microbial cultures of the fed-batch type, using mainly microbial growth data. This objective was achieved using dielectric spectroscopy technology for online monitoring of microbial growth and hybrid neural networks for online prediction of substrate concentration. The glucose estimator was integrated to a fuzzy logic controller to control the substrate concentration in a fed-batch experiment. Dielectric spectroscopy is a technology sensitive to the air volume fraction in the culture media and the turbulence generated by the agitation; however, the introduction of a polynomial function for the calibration of the permittivity signal allowed biomass estimations with an approximation error of 2%. The methodology presented in this work was successfully implemented for the glucose prediction and control of a fed-batch culture of Bacillus thuringiensis with an approximation error of 6%.
在生物过程工程中，实验测量通常是建模工作中昂贵的一部分；因此，需要不断开发更便宜、更简单、更高效的方法来利用可用的信息。本工作的目的是开发一种软传感器，该传感器具有使用主要微生物生长数据可靠地预测和控制分批补料型微生物培养物中的基质的能力。这一目标是通过介电谱技术在线监测微生物生长和混合神经网络在线预测基质浓度来实现的。葡萄糖估计器被集成到模糊逻辑控制器中，以控制分批实验中的基质浓度。介电谱技术对培养基中的空气体积分数和搅拌产生的湍流敏感；然而，通过引入一个多项式函数来校准介电常数信号，允许用近似误差为 2%的方法来估计生物量。本文提出的方法成功地应用于苏云金芽孢杆菌分批补料培养物的葡萄糖预测和控制，其近似误差为 6%。
