Open AccessRobust dynamic experiments for the precise estimation of respiration and fermentation parameters of fruit and vegetables
Author(s) -
Arno Strouwen,
Bart Nicolaı̈,
Peter Goos
Publication year - 2022
Publication title -
plos computational biology/plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1009610
Subject(s) - pear , biological system , respiration , fermentation , estimation theory , computer science , identification (biology) , biochemical engineering , mathematics , chemistry , algorithm , biology , botany , food science , engineering , world wide web
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 O 2 and CO 2 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.