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On-line Monitoring of Penicillin G Acylase (PGA) Production Using a Fuzzy Logic Algorithm

机译:使用模糊逻辑算法在线监测青霉素G酰化酶(PGA)生产

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The ability to control bioprocesses at their optimal states is of considerable interest to modern fermentation industries. The aim is to reduce production costs and increase yield while at the same time maintaining the quality of the metabolic products. The objetive of this paper is to apply fuzzy logic to the Penicillin G acylase (PGA) production process. PGA hydrolyzes penicillin G to yield 6-aminopenicilanic acid (6-APA) and phenyl acetic acid. 6-APA is an important raw material, used to produce semi-synthetic β-lactam antibiotics. Ten experiments were carried out in a bench-scale bioreactor with diferent experimental conditions. Several variables were tested to identify the best fuzzy inputs. The results show that batch time, carbon dioxide concentration and its derivate were the best choice. The algorithm employs these on-line measurements to infer the optimal interval to stop the cultivation. The fuzzy algorithm could accurately infer the time for bioreactor harvesting and the output linguistic variable “stop cultivation” was defined between 0 and 100% certainty. The best experimental result was obtained when the dissolved oxygen concentration was maintained close to 0.5% of saturation.
机译:在现代发酵工业中,将生物过程控制在最佳状态的能力备受关注。目的是降低生产成本并增加产量,同时保持代谢产物的质量。本文的目的是将模糊逻辑应用于青霉素G酰基转移酶(PGA)的生产过程。 PGA水解青霉素G,得到6-氨基青苯二酸(6-APA)和苯乙酸。 6-APA是重要的原料,用于生产半合成的β-内酰胺类抗生素。在具有不同实验条件的台式生物反应器中进行了十项实验。测试了几个变量以识别最佳模糊输入。结果表明,批处理时间,二氧化碳浓度及其衍生物是最佳选择。该算法使用这些在线测量值来推断最佳间隔以停止培养。模糊算法可以准确地推断出生物反应器的收获时间,并且将输出语言变量“停止培养”定义为0至100%的确定性。当溶解氧浓度保持在接近饱和度的0.5%时,可获得最佳实验结果。

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