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Characterization of Polylactic Acid Biocomposites Filled with Native Starch Granules from Dioscorea remotiflora Tubers

Biocomposites were fabricated utilizing polylactic acid (PLA) combined with native starch sourced from mountain’s yam (Dioscorea remotiflora Knuth), an underexplored tuber variety. Different starch compositions (7.5, 15.0, 22.5, and 30.0 wt.%) were blended with PLA in a batch mixer at 160 °C to produce PLA/starch biocomposites. The biocomposites were characterized by analyzing their morphology, particle size distribution, thermal, X-ray diffraction (XDR), mechanical, and dynamic mechanical (DMA) properties, water absorption behavior, and color. The results showed that the amylose content of Dioscorea remotiflora starch was 48.43 ± 1.4%, which corresponds to a high-amylose starch (>30% of amylose). Particle size analysis showed large z-average particle diameters (Dz0) of the starch granules (30.59 ± 3.44 μm). Scanning electron microscopy (SEM) images showed oval-shaped granules evenly distributed throughout the structure of the biocomposite, without observable agglomeration or damage to its structure. XDR and DMA analyses revealed an increase in the crystallinity of the biocomposites as the proportion of the starch increased. The tensile modulus (E) underwent a reduction, whereas the flexural modulus (Eflex) increased with the amount of starch incorporated. The biocomposites with the highest Eflex were those with a starch content of 22.5 wt.%, which increased by 8.7% compared to the neat PLA. The water absorption of the biocomposites demonstrated a higher uptake capacity as the starch content increased. The rate of water absorption in the biocomposites followed the principles of Fick’s Law. The novelty of this work lies in its offering an alternative for the use of high-amylose mountain’s yam starch to produce low-cost bioplastics for different applications.

Publication date: 25/03/2024

Author: Yokiushirdhilgilmara Estrada-Girón

Reference: doi: 10.3390/polym16070899

MDPI (polymers)


This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870292.