ENBIS Spring Meeting 2018

4 – 6 June 2018; Florence, Italy Abstract submission: 17 November 2017 – 20 April 2018

Optimizing an oxygen input profile to estimate Michaelis-Menten respiration parameters

4 June 2018, 16:40 – 17:05


Submitted by
Arno Strouwen
Arno Strouwen (Department of Biosystems, KU Leuven), Bart Nicolaï (Department of Biosystems, KU Leuven), Peter Goos (Department of Biosystems, KU Leuven)
Fresh fruits and vegetables are perishable products and need to be stored at appropriate temperature, oxygen and carbon dioxide conditions, after their harvest. Traditionally, this is achieved by independently storing the product at many different combinations of temperature as well as O2 and CO2 partial pressures. The optimal storage conditions are then inferred from traditional response surface modeling. This method is labor intensive, due to the larger number of experimental combinations that have to be tested.

Many modern fruit and vegetable storage applications, such as modified atmosphere packaging (MAP) and dynamic controlled atmosphere (DCA), rely on knowledge of mass balances, transport phenomena and reaction kinetics, and use comprehensive mathematical models that describe the behavior of the product as a dynamical system with inputs (temperature, oxygen and carbon dioxide partial pressures) and outputs (respiration and fermentation rate, quality attributes). A key feature of such dynamic models is the respiration kinetics, which is generally described by a non-linear model of the Michaelis-Menten type. The shift from traditional response surface modeling towards dynamic models for estimating respiration kinetics entails major challenges for designing experiments. For example, quantifying and optimizing the information content of experiments is numerically more complex. This is due to the fact that the dynamic approach involves differential equations and non-linear parameter estimation.

In this presentation, we optimize a time varying oxygen input profile to estimate the respiration kinetics of pear fruit. To optimize the information content produced by this oxygen profile, we apply optimal dynamic experimental design principles and present a modified coordinate-exchange algorithm to achieve this goal. Finally, we compare the optimal input profiles to several benchmark approaches.

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