Author:

Keywords:

Science & Technology, Life Sciences & Biomedicine, Biochemical Research Methods, Mathematical & Computational Biology, Biochemistry & Molecular Biology, OPTIMAL EXPERIMENTAL-DESIGN, NUMERICAL-METHODS, GROWTH-KINETICS, MODEL, SYSTEMS, Carbon Dioxide, Cell Respiration, Computational Biology, Fermentation, Fruit, Kinetics, Models, Biological, Oxygen, Vegetables, C16/16/002#53766054, 01 Mathematical Sciences, 06 Biological Sciences, 08 Information and Computing Sciences, Bioinformatics

Abstract:

Dynamic models based on non-linear differential equations are increasingly being used in many biological applications. Highly informative dynamic experiments are valuable for the identification of these dynamic models. The storage of fresh fruit and vegetables is one such application where dynamic experimentation is gaining momentum. In this paper, we construct optimal O2 and CO2 gas input profiles to estimate the respiration and fermentation kinetics of pear fruit. The optimal input profiles, however, depend on the true values of the respiration and fermentation parameters. Locally optimal design of input profiles, which uses a single initial guess for the parameters, is the traditional method to deal with this issue. This method, however, is very sensitive to the initial values selected for the model parameters. Therefore, we present a robust experimental design approach that can handle uncertainty on the model parameters.