The calculation of metabolic turnover rates is essential for the scalable design, analysis and control of bioprocesses. A novel rate calculation algorithm is presented that is based on the dynamic adaptation of window sizes in order to deliver robust and precise rates with uniform signal-to-noise ratios. Additionally a model-based generic algorithm for deriving optimal rate calculation workflows was developed. The generic algorithms delivered more precise and accurate rates for online and offline signals, which was demonstrated for both in silico- and real batch and fed-batch fermentation process data. The presented algorithms will strongly support bioprocess development and control as enabling tools for multivariate data analysis, mechanistic modeling and dynamic experimentation.