A Framework for Digital Technologies Application in Soft Sensing Monitoring to Recombinant Nanobody Production in <i>Escherichia coli</i>: From Model Explanation to the Study of Potential Scenario.

An analysis of the overall results of all models trained to estimate protein and biomass concentrations reveals a clear trend.

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For the glucose fed setup, a positive trend was observed, and notably, values were mainly concentrated around 0 (9.005 g/h) (Values used to standardize the glucose fed setup in the training data set: μ Glucose Fed Setup, exp = 9.005 g/h, σ Glucose Fed Setup,exp = 9.799 g/h).

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Other correlations reached Pearson coefficients between 0.72 and 0.75, such as temperature–substrate weight ( r Temperature, Substrate Weight = 0.75), temperature–BAST ( r Temperature, BAST = −0.74), pO 2 –glucose feed setup ( r pO2, Glucose Feed Setup = −0.72), and glucose added–base weight ( r Glucose Added, Base Weight = −0.72). However, graphical analysis shows that although a slight trend may be present, it is not as clearly defined as in the variables with Pearson coefficients greater than 0.8.

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