{"title":"On-Line, Real-Time Measurements of Cellular Biomass using Dielectric Spectroscopy","authors":"J. Yardley, D. Kell, J. Barrett, C. Davey","doi":"10.1080/02648725.2000.10647986","DOIUrl":null,"url":null,"abstract":"Introduction All else being equal, the productivity of a biological process is determined by the quantity of biomass present. There is therefore a major requirement for the accurate measurement and control of the biomass within fermentors, at both laboratory and industrial scales. Presently the range of sensors available that can be used in situ and reliably for the monitoring and regulation of biotechnological processes in general is rather limited. These sensors normally rely upon physical (e.g. optical, mechanical and electrical) or chemical variables (e.g. pH and concentration) rather than biological ones per se (Sarra et al., 1996; Pons, 1991). However only physical methods allow the on-line, real-time estimation of biomass (Harris and Kell, 1985). As well as physical methods, any easily determinable chemical that is produced or consumed by cells at an essentially constant rate during cell growth may also be used to assess biomass, e.g. carbon dioxide evolution and oxygen consumption. In these indirect methods biomass is then calculated based upon mass balances, stoichiometric relationships or empirical constants. However, this type of approach has the great disadvantage that it does not generally discriminate between biomass and necromass (Kell et al., 1990). Even if biomass was easily measurable there is still the question of what is biologically relevant information for fermentation control and how can one define and quantify it (e.g. metabolism, viability, vitality, morphology) (Kell et al., 1987; Kell, 1987a;","PeriodicalId":8931,"journal":{"name":"Biotechnology and Genetic Engineering Reviews","volume":"6 1","pages":"3 - 36"},"PeriodicalIF":0.0000,"publicationDate":"2000-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"96","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biotechnology and Genetic Engineering Reviews","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/02648725.2000.10647986","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 96
Abstract
Introduction All else being equal, the productivity of a biological process is determined by the quantity of biomass present. There is therefore a major requirement for the accurate measurement and control of the biomass within fermentors, at both laboratory and industrial scales. Presently the range of sensors available that can be used in situ and reliably for the monitoring and regulation of biotechnological processes in general is rather limited. These sensors normally rely upon physical (e.g. optical, mechanical and electrical) or chemical variables (e.g. pH and concentration) rather than biological ones per se (Sarra et al., 1996; Pons, 1991). However only physical methods allow the on-line, real-time estimation of biomass (Harris and Kell, 1985). As well as physical methods, any easily determinable chemical that is produced or consumed by cells at an essentially constant rate during cell growth may also be used to assess biomass, e.g. carbon dioxide evolution and oxygen consumption. In these indirect methods biomass is then calculated based upon mass balances, stoichiometric relationships or empirical constants. However, this type of approach has the great disadvantage that it does not generally discriminate between biomass and necromass (Kell et al., 1990). Even if biomass was easily measurable there is still the question of what is biologically relevant information for fermentation control and how can one define and quantify it (e.g. metabolism, viability, vitality, morphology) (Kell et al., 1987; Kell, 1987a;
在其他条件相同的情况下,生物过程的生产率取决于存在的生物量的数量。因此,在实验室和工业规模上,对发酵罐内生物量的精确测量和控制是一个主要的要求。目前,一般来说,可在现场可靠地用于监测和调节生物技术过程的传感器的范围相当有限。这些传感器通常依赖物理(如光学、机械和电气)或化学变量(如pH值和浓度),而不是生物变量本身(Sarra等人,1996年;脑桥,1991)。然而,只有物理方法允许在线实时估算生物量(Harris和Kell, 1985)。除了物理方法外,细胞在生长过程中以基本恒定的速率产生或消耗的任何易于确定的化学物质也可用于评估生物量,例如二氧化碳演变和氧气消耗。在这些间接方法中,生物量是根据质量平衡、化学计量关系或经验常数来计算的。然而,这种方法有一个很大的缺点,即它通常不能区分生物量和坏死体(Kell et al., 1990)。即使生物量很容易测量,仍然存在一个问题,即什么是发酵控制的生物学相关信息,以及如何定义和量化它(例如代谢、活力、活力、形态)(Kell等人,1987;凯尔,1987;