<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Meshram, Mukesh</style></author><author><style face="normal" font="default" size="100%">Kulkarni, Abhijit</style></author><author><style face="normal" font="default" size="100%">Jayaraman, Valadi K.</style></author><author><style face="normal" font="default" size="100%">Kulkarni, B. D.</style></author><author><style face="normal" font="default" size="100%">Lele, S. S.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Optimal xylanase production using Penicilium janthinellum NCIM 1169: a model based approach</style></title><secondary-title><style face="normal" font="default" size="100%">Biochemical Engineering Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Artificial intelligence</style></keyword><keyword><style  face="normal" font="default" size="100%">Enzyme activity</style></keyword><keyword><style  face="normal" font="default" size="100%">Fermentation</style></keyword><keyword><style  face="normal" font="default" size="100%">Modeling</style></keyword><keyword><style  face="normal" font="default" size="100%">Optimization</style></keyword><keyword><style  face="normal" font="default" size="100%">Xylanase</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JUN</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">2</style></number><publisher><style face="normal" font="default" size="100%">ELSEVIER SCIENCE SA</style></publisher><pub-location><style face="normal" font="default" size="100%">PO BOX 564, 1001 LAUSANNE, SWITZERLAND</style></pub-location><volume><style face="normal" font="default" size="100%">40</style></volume><pages><style face="normal" font="default" size="100%">348-356</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Xylanases are an industrially important class of hydrolytic enzymes that degrade xylans. Production of xylanase from a fungal culture by submerged fermentation and optimization of the operating conditions for maximum activity are the two aims of the present study. Penicillium janthinellum NCIM 1169 with Mandels-Weber medium, sugarcane bagassse (40\#) as a carbon source and beef extract as a nitrogen source were used in the experiments. We did 41 experiments to see the effect of variations in carbon, nitrogen source, pH, and inoculum on xylanase activity. This data was then used to build an input/output model using multiple linear regression, back propagation neural network and lazy learning algorithm. It was found that lazy learning model correlated well in mapping input/output data. This model was then utilized as an objective function in genetic algorithm to find the optimal combination of the operating conditions to get the maximum xylanase activity. It was observed that with carbon source, 1.63%, nitrogen source, 0.16%, pH, 4.1, and inoculum, 5.5%, maximum xylanase activity of 28.98 +/- 1.73 U/ml was achieved. (C) 2008 Elsevier B.V. All rights reserved.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">2.692</style></custom4></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Katre, Gouri</style></author><author><style face="normal" font="default" size="100%">Raskar, Shubham</style></author><author><style face="normal" font="default" size="100%">Zinjarde, Smita</style></author><author><style face="normal" font="default" size="100%">Kumar, V. Ravi</style></author><author><style face="normal" font="default" size="100%">Kulkarni, B. D.</style></author><author><style face="normal" font="default" size="100%">RaviKumar, Ameeta</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Optimization of the in situ transesterification step for biodiesel production using biomass of Yarrowia lipolytica NCIM 3589 grown on waste cooking oil</style></title><secondary-title><style face="normal" font="default" size="100%">Energy</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biodiesel</style></keyword><keyword><style  face="normal" font="default" size="100%">FAME</style></keyword><keyword><style  face="normal" font="default" size="100%">In situ transesterification</style></keyword><keyword><style  face="normal" font="default" size="100%">One -step</style></keyword><keyword><style  face="normal" font="default" size="100%">Waste cooking oil</style></keyword><keyword><style  face="normal" font="default" size="100%">Yarrowia lipolytica</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2018</style></year><pub-dates><date><style  face="normal" font="default" size="100%">JAN </style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">142</style></volume><pages><style face="normal" font="default" size="100%">944-952</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The in situ (one-step) acid-catalyzed transesterification step for conversion to biodiesel of biomass from oleaginous yeast Yarrowia lipolytica grown on waste cooking oil (WCO) is studied. The process yield of biodiesel was optimized by investigating effects of various parameters, namely, biomass, methanol, chloroform, catalyst, temperature, time and sonication. A Plackett-Burman statistical design of experiments revealed that biomass is the most significant factor influencing biodiesel (FAME, fatty acid methyl ester) production. Subsequently, a one variable design (OVD) of experiments for increased biomass loadings showed higher yields of FAME with no additional requirement of reactants, solvents or special equipment. The biomass grown on WCO had a lipid productivity of 0.042 g L-1 h(-1) and 4 g of this loading gave a high FAME yield of 0.88 gin 8 hat 50 degrees C with methanol: chloroform (10:1) and acid catalyst (0.2 M H2SO4,1.0 ml g(-1)). The FAME profile had desirable amounts of saturated (32.81%), monounsaturated (36.41%), polyunsaturated (30.59%) methyl esters. The predicted and experimentally determined physico-chemical properties of FAME were found in accordance with specified international standards. Thus, the direct one-pot in situ transesterification reaction using Y. lipolytica biomass grown on WCO provides a high yield of biodiesel with potential applicability while simultaneously addressing the management of this pollutant. (C) 2017 Elsevier Ltd. All rights reserved.&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">Article</style></work-type><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">4.520</style></custom4></record></records></xml>