当社グループは 3,000 以上の世界的なカンファレンスシリーズ 米国、ヨーロッパ、世界中で毎年イベントが開催されます。 1,000 のより科学的な学会からの支援を受けたアジア および 700 以上の オープン アクセスを発行ジャーナルには 50,000 人以上の著名人が掲載されており、科学者が編集委員として名高い
。オープンアクセスジャーナルはより多くの読者と引用を獲得
700 ジャーナル と 15,000,000 人の読者 各ジャーナルは 25,000 人以上の読者を獲得
Khurram Shahzad Baig
In most of the developed countries, the most of the transport running is on some form of biofuel. The main feedstocks used to produces biofuel are wheat and corn grans. The addition of bioethanol into motor fuels has increased the pressure to the grains supply market and food prices are on the increase due to a relation with the grains prices. A use of waste lignocellulosic materials (agricultural waste and /or forestry waste) would release this pressure.
The cost of biofuel production is based on the costs of two main reactant materials i) lignocellulosic materials, ii) enzymes. The cost of enzymes can be reduced by reuse of them. Apart from the redesigning of enzymes to increase enzymes stability at elevated temperature etc., it is also important to look into the optimization of operating parameters. The optimization of the adsorption parameters was performed by using statistical analysis tools such as Response Surface Methodology (RSM) and Restricted Maximum Likelihood Estimation (RMLE). The obtained binomial quadratic model predicted almost the same values of the cellulases adsorbed as that of experimental values within a percent error of x±6. The optimized values of the operating parameters were modified according to available practical knowledge and the model was validated. It was found to be in the agreement of the experimental values. The optimized conditions would help biofuel industry in designing their production process.
Highlights
The operating parameters for enzymatic adsorption such as adsorption temperature, enzymes concentration, and incubation time were optimized for production of biofuel.
The RSM response equation can be used for controlling efficiency of the adsorption reaction with multiple variables.
The interaction of operating parameters for the enzymatic adsorption and its efficiency was systemically analyzed for the first time using RSM and REML methods.