Pandiyan K, Tiwari Rameshwar, Singh Surender, Nain Pawan K S, Rana Sarika, Arora Anju, Singh Shashi B, Nain Lata
Division of Microbiology, Indian Agricultural Research Institute, New Delhi 110012, India.
School of Civil & Mechanical Engineering, Galgotias University, Greater Noida, Uttar Pradesh 201306, India.
Enzyme Res. 2014;2014:764898. doi: 10.1155/2014/764898. Epub 2014 May 12.
Parthenium sp. is a noxious weed which threatens the environment and biodiversity due to its rapid invasion. This lignocellulosic weed was investigated for its potential in biofuel production by subjecting it to mild alkali pretreatment followed by enzymatic saccharification which resulted in significant amount of fermentable sugar yield (76.6%). Optimization of enzymatic hydrolysis variables such as temperature, pH, enzyme, and substrate loading was carried out using central composite design (CCD) in response to surface methodology (RSM) to achieve the maximum saccharification yield. Data obtained from RSM was validated using ANOVA. After the optimization process, a model was proposed with predicted value of 80.08% saccharification yield under optimum conditions which was confirmed by the experimental value of 85.80%. This illustrated a good agreement between predicted and experimental response (saccharification yield). The saccharification yield was enhanced by enzyme loading and reduced by temperature and substrate loading. This study reveals that under optimized condition, sugar yield was significantly increased which was higher than earlier reports and promises the use of Parthenium sp. biomass as a feedstock for bioethanol production.
银胶菊是一种有害杂草,因其迅速蔓延而对环境和生物多样性构成威胁。对这种木质纤维素杂草进行了生物燃料生产潜力的研究,先对其进行温和碱预处理,然后进行酶糖化,可得到大量可发酵糖产量(76.6%)。使用响应面法(RSM)中的中心复合设计(CCD)对酶水解变量(如温度、pH值、酶和底物负载量)进行优化,以实现最大糖化产量。使用方差分析(ANOVA)对从RSM获得的数据进行验证。优化过程后,提出了一个模型,在最佳条件下预测糖化产量值为80.08%,实验值为85.80%,这证实了该模型。这表明预测响应与实验响应(糖化产量)之间具有良好的一致性。糖化产量随酶负载量增加而提高,随温度和底物负载量降低。本研究表明,在优化条件下,糖产量显著增加,高于早期报道,并有望将银胶菊生物质用作生物乙醇生产的原料。