Vacuum Foam-Mat Drying of Red Palm Oil NLC: A Fractional Factorial Screening

Abdi Redha; Saniah; Lidia Chronika Simanjuntak

doi:10.59890/ijsr.v4i1.272

Authors

Abdi Redha Department of Integrated Plantation Product Processing, State Polytechnic of Pontianak
Saniah Department of Integrated Plantation Product Processing, State Polytechnic of Pontianak
Lidia Chronika Simanjuntak Department of Integrated Plantation Product Processing, State Polytechnic of Pontianak

DOI:

https://doi.org/10.59890/ijsr.v4i1.272

Keywords:

Nanostructured Lipid Carriers, Vacuum Foam-Mat Drying, Red Palm Oil, Fractional Factorial Design, Palmitate Content

Abstract

Nanostructured lipid carriers (NLC) derived from red palm oil (RPO) offer promising delivery systems for bioactive compounds, yet their aqueous dispersions remain thermodynamically unstable during extended storage. Vacuum foam-mat drying presents a viable solution for converting liquid NLC into stable powder form while preserving heat-sensitive bioactives at moderate temperatures (50–70°C). This study aimed to systematically identify critical process parameters affecting vacuum foam-mat drying of RPO-based NLC using a Minimum Run Resolution IV fractional factorial design. Five factors were investigated: NLC-to-maltodextrin ratio, maltodextrin concentration, Tween 80 concentration, stirring temperature, and oven temperature, evaluated across 12 experimental runs. Results revealed that the NLC-to-maltodextrin ratio significantly influenced powder yield (66.03–84.95%), while Tween 80 concentration predominantly affected moisture content (8.19–12.87%) and palmitate retention (20.3–110 ppm). Oven temperature emerged as the primary factor controlling particle diameter (400–550 µm) and could induce palmitate degradation at elevated levels. Significant two-factor interactions were observed, particularly between maltodextrin concentration and stirring temperature, affecting palmitate preservation. This screening design effectively reduced the number of experimental runs from 32 to 12 while maintaining a reliable estimation of main effects, providing a foundation for subsequent Response Surface Methodology optimization.

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