Structural identifiability of a model for the acetic acid fermentation process

Area of Science:

• Biotechnology
• Process Engineering
• Mathematical Modelling

Background:

• Modelling is crucial for optimizing and controlling biotechnological processes.
• Parameter estimation is a key step in developing these models.
• Model identifiability analysis ensures parameters are uniquely determinable and physically meaningful.

Purpose of the Study:

• To discuss the theoretical identifiability of a novel acetic acid fermentation model.
• To review existing methodologies for assessing model identifiability.

Main Methods:

• Focus on theoretical (structural) identifiability, which depends solely on model structure.
• Contrast with practical identifiability, which considers experimental data quantity and quality.
• Review of established identifiability analysis techniques.

Main Results:

• Discussion of the theoretical identifiability properties of the proposed acetic acid fermentation model.
• Evaluation of the applicability of existing identifiability methods to this specific model.

Conclusions:

• Theoretical identifiability is a fundamental prerequisite for developing reliable biotechnological models.
• Understanding identifiability ensures that model parameters yield meaningful physical interpretations.
• The study contributes to the robust development of acetic acid fermentation models through rigorous identifiability assessment.