Comparison of regression and design models for biosorption process

Cetintas S., Elevli S., BİNGÖL D.

DESALINATION AND WATER TREATMENT, vol.145, pp.107-119, 2019 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 145
  • Publication Date: 2019
  • Doi Number: 10.5004/dwt.2019.23647
  • Journal Name: DESALINATION AND WATER TREATMENT
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.107-119
  • Keywords: Biosorption, Box-Behnken design (BBD), Central composite design (CCD), Full factorial design (FFD), Multi linear regression (MLR), RESPONSE-SURFACE METHODOLOGY, CENTRAL COMPOSITE DESIGN, AQUEOUS-SOLUTIONS, COPPER REMOVAL, HEAVY-METALS, OPTIMIZATION, CU(II), ADSORPTION, IONS, PREDICTION
  • Ondokuz Mayıs University Affiliated: Yes

Abstract

In this study, the biosorption process were optimized and compared for the first time in terms of their accuracy and predictive ability for the sorption of Cu(II) ions onto date palm (Phoenix dactylifera L.) seeds used as an agricultural waste product by using four models, multi-linear regression (MLR), full factorial design with center points (FFD), Box-Behnken design (BBD) and central composite design (CCD). The responses were evaluated based on the regression equations formulated according to the results of the analyses of models. It was found that MLR and FFD models had a lower predictive capability than response surface methodologies (RSM).