Optimization of Maltodextrin Production from Pineapple Stem Waste Using Response Surface Methodology

Parlan Parlan, Bambang Nurhadi

Abstract


The enzymatic hydrolysis of starch from pineapple stem waste for maltodextrin production was successfully optimized using Response Surface Methodology (RSM). The study identified enzyme concentration and hydrolysis time as critical factors significantly influencing reducing sugar concentration and DE values. Under the optimal conditions (16 µL enzyme/30 gram of dry starch and 30 minutes hydrolysis time), the model predicted a reducing sugar concentration of 13.9%. However, the experimental validation produced an actual yield of 13.21%. The model RSM demonstrated a reliability level of 95.05% (moderately accurate), with deviations primarily due to experimental variability and model limitations. ANOVA analysis confirmed the model's validity with an R² value of 0.9873, while residual analyses supported its adequacy and predictive accuracy. The 3D surface response analysis highlighted the critical thresholds for optimizing reducing sugar production. This study provides a sustainable solution for valorizing pineapple stem waste into industrially valuable maltodextrin, supporting environmental conservation and the circular economy. Further studies are recommended to investigate the impact of enzyme characteristics, substrate pretreatment methods, and large-scale process validation to enhance the efficiency and commercial viability of maltodextrin production from pineapple stem waste.


Keywords


Dextrose equivalent (DE); maltodextrin; pineapple stem waste; response surface methodology (rsm); starch hydrolysis

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DOI: https://doi.org/10.24198/jt.vol19n1.10

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