• Title of article

    Optimization of Ultrasound-Assisted Extraction of Polyphenol Content from Zea mays Hairs (Waste)

  • Author/Authors

    Aourabi, Sarra Laboratory of Engineering - Modeling and Systems Analysis (LIMAS) - University of Sidi Mohamed Ben Abdellah (USMBA) - Faculty of Sciences - PO Box 1796-30000 - Fez-Atlas - Morocco , Sfaira, Mouhcine Laboratory of Engineering - Modeling and Systems Analysis (LIMAS) - University of Sidi Mohamed Ben Abdellah (USMBA) - Faculty of Sciences - PO Box 1796-30000 - Fez-Atlas - Morocco , Mahjoubi, Fatima Laboratory of Engineering - Modeling and Systems Analysis (LIMAS) - University of Sidi Mohamed Ben Abdellah (USMBA) - Faculty of Sciences - PO Box 1796-30000 - Fez-Atlas - Morocco

  • Pages
    10
  • From page
    1
  • To page
    10
  • Abstract
    The aim of this study was to achieve the best extraction efficiency of the hydroethanolic extract of Zea mays hairs. The impacts of ethanol concentration, extraction time, and solvent /material ratio were studied in relation to the performance of Zea mays extracts by ultrasonic extraction at 50 kHz and room temperature. All extracts were quantitatively characterized in terms of polyphenol content. Response surface methodology (RSM) was carried out to optimize the extraction process and increase extraction efficiency. In the experiments, different concentrations of ethanol:water were used. The efficiency of the extraction process was determined from an analysis of variance (ANOVA). The maximum extraction efficiency of the hydroethanolic extraction (31.37%) and the quantitative value of the polyphenol content (257.87 mg EAG/g extract) were obtained using a treatment time of 40 min, an ethanol:water (70 : 30), and a solvent/material ratio (11 mL/g). The results obtained indicate that ultrasonic-assisted extraction is an effective method for extracting natural compounds from Zea mays, thus allowing the full use of this abundant and inexpensive industrial waste.
  • Keywords
    Response surface methodology (RSM) , ANOVA , Optimization , Zea mays Hairs (Waste)
  • Journal title
    The Scientific World Journal
  • Serial Year
    2020
  • Record number

    2616656