PRODUCTION OF BIOETHANOL USING LIGNOCELLULOSIC BIOMASS

Abstract

Fast declining fossil fuels, acute energy crisis energy, a spike in greenhouse gas emissions, and various environmental problems had led to a search for sustainable biofuels production. Extensive research is done in the field of biofuels such as bioethanol due to energy security, low environmental pollution effects, and cost benefits. The bioethanol production process has some necessary steps: pretreatment process, enzymatic hydrolysis, fermentation, distillation, and drying. The conventional ethanol-producing substances are consumable food-based material. Nowadays, attention has been searched for a new alternative to raw material (i.e., nonfood based material) due to the world food crisis. Microorganisms have received much attention for biofuel production through lignocellulosic feedstocks. They secrete collaborative enzymes for digesting the lignocellulosic biomass to simple sugars and afterward fermenting them to alcohol. Other fuels are produced from the same feedstocks as bioethanol. Still, it faces challenges compared to its production processes, such as the price of raw material, pretreatment methods, enzymatic hydrolysis, and low tolerance of the fermenting strain leading to its fewer yields, downstream processing, production of undesired solvents, and fermentation inhibitors. So a new promising biofuel as bioethanol has taken a great attraction of the researchers due to its competitive properties compared to gasoline. The research and development on bioethanol as a gasoline substitute indicates that it is a representative renewable energy source, able to elevate engine performance, combustion and also reduce greenhouse gas emissions. In present research, the duckweed (Lemna minor, Family-Lemnaceae) has been highlighted as a feasible feedstock due to its rapid growth rate and adaptability in various aquatic environments. Its biochemical makeup, characterized by high starch content and low lignin content, allows for effective fermentation and saccharification. Duckweed offers numerous advantages, including minimal land use, considerable biomass output, and wastewater treatment. The paper highlights the potential of duckweed, specifically Lemna minor, as a sustainable source of bioethanol. Its advantageous characteristics like non-food feedstock, fastest growing angiosperm, v global adaptability across the world climates, assimilation of high starch with some nutrient modification, and less or no lignin content, make it a suitable candidate for bioethanol production. This research includes the production of starch-enhanced Lemna minor in nutrition starvation conditions for bioethanol production from it. The starch enhancement technique was standardized by performing experiments sequentially with organic manure, nitrogen-free Hoagland media and full-strength Hoagland media. Initially, the starch quantity was found to be 7% but it has been observed that during nitrogen stress, high starch accumulation was observed in Lemna minor, and on the 9th day it was found to be maximum, which was 26 % with standard deviation± 0.3. It was also observed that protein, glucose, and fructose composition were dropped during this experiment. One-way ANOVA analysis was performed for statistical analysis. It has been found that during the starch enhancement experiment, the starch level was significantly (P < 0.05) higher in nitrogen-free Hoagland media compared to the organic manure and full-strength Hoagland media. So Lemna minor During ethanol production amylase is commonly used enzyme to saccharify the raw plant biomass. This research mainly entailed the collection and preparation of raw materials, maintenance of microorganisms, and optimization of physical and chemical variables for the production of amylolytic cocktail and ethanol. OFAT determined the significant components that influenced the yield of enzymatic activity and ethanol. RSM with CCD was used to determine the influences between factors to obtain the highest yields of enzymes and ethanol. ANOVA was done to examine the significance of factor interactions while response surface plots showed how different factors affected enzyme reaction. Aspergillus niger MTCC-12987, Saccharomyces cereviceaeMTCC-171, and Candida shehatae MTCC-12913 were used for amylolytic cocktail and ethanol production respectively. Minitab 22 software was employed and response surface regression with Central composite design was used to examined an optimized process for maximum yield of enzyme activity and ethanol production. The highest enzyme activity value predicted by the software is 1063.81U/ml, which was closer to the experimental value of 1072.4 U/ml. Again the maximum ethanol production predicted by software is 11.83 % was closer to the experimental value of 10.77 %. Thus, the experimental performance under optimal conditions fitted the model's predictions fairly close. For the purpose to evaluate the combined effects of all independent variables in a fermentation process that may have developed from their interaction with one another, the RSM methodology has been employed as an alternative tool for statistical analysis.