Data-driven intelligent modeling, optimization, and global sensitivity analysis of a xanthan gum biosynthesis process.

In this study, the focus was to produce xanthan gum from pineapple waste using . Six machine learning models were employed to optimize fermentation time and key metabolic stimulants (KHPO and NHNO). The production of xanthan gum was optimized using two evolutionary optimization algorithms, particle swarm optimization, and genetic algorithm while the importance of input features was ranked using global sensitivity analysis.