title: Optimization of delignification of two Pennisetum grass species by NaOH pretreatment using Taguchi and ANN statistical approach.
abstract: In the bioconversion of lignocelluloses for bioethanol, pretreatment seems to be the most important step which improves the elimination of the lignin and hemicelluloses content, exposing cellulose to further hydrolysis. The present study discusses the application of dynamic statistical techniques like the Taguchi method and artificial neural network (ANN) in the optimization of pretreatment of lignocellulosic biomasses such as Hybrid Napier grass (HNG) (Pennisetum purpureum) and Denanath grass (DG) (Pennisetum pedicellatum), using alkali sodium hydroxide. This study analysed and determined a parameter combination with a low number of experiments by using the Taguchi method in which both the substrates can be efficiently pretreated. The optimized parameters obtained from the L16 orthogonal array are soaking time (18 and 26 h), temperature (60°C and 55°C), and alkali concentration (1%) for HNG and DG, respectively. High performance liquid chromatography analysis of the optimized pretreated grass varieties confirmed the presence of glucan (47.94% and 46.50%), xylan (9.35% and 7.95%), arabinan (2.15% and 2.2%), and galactan/mannan (1.44% and 1.52%) for HNG and DG, respectively. Physicochemical characterization studies of native and alkali-pretreated grasses were carried out by scanning electron microscopy and Fourier transformation Infrared spectroscopy which revealed some morphological differences between the native and optimized pretreated samples. Model validation by ANN showed a good agreement between experimental results and the predicted responses.
authors.affiliation: a Department of Biotechnology, College of Engineering and Technology , Biju Patnaik University of Technology , Bhubaneswar, India.
authors.forename: Sonali
authors.initials: S
authors.lastname: Mohaptra
authors.affiliation: a Department of Biotechnology, College of Engineering and Technology , Biju Patnaik University of Technology , Bhubaneswar, India.
authors.forename: Preeti Krishna
authors.initials: PK
authors.lastname: Dash
authors.affiliation: b Department of Biotechnology and Medical Engineering , National Institute of Technology , Rourkela, India.
authors.forename: Sudhanshu Shekar
authors.initials: SS
authors.lastname: Behera
authors.affiliation: a Department of Biotechnology, College of Engineering and Technology , Biju Patnaik University of Technology , Bhubaneswar, India.
authors.forename: Hrudayanath
authors.initials: H
authors.lastname: Thatoi
mesh_terms: D002482:Cellulose / Q000737:chemistry*; D002851:Chromatography, High Pressure Liquid; D008855:Microscopy, Electron, Scanning; D016571:Neural Networks, Computer; D031782:Pennisetum / Q000737:chemistry* / Q000648:ultrastructure; D012972:Sodium Hydroxide / Q000737:chemistry*; D017550:Spectroscopy, Fourier Transform Infrared; D013696:Temperature
chemical_list: D012972:Sodium Hydroxide; D002482:Cellulose
keywords: ANN; Lignocellulose; Pennisetum pedicellatum; Pennisetum purpureum; Taguchi design