R
Rintu Banerjee
Researcher at Indian Institute of Technology Kharagpur
Publications - 230
Citations - 7707
Rintu Banerjee is an academic researcher from Indian Institute of Technology Kharagpur. The author has contributed to research in topics: Rhizopus oryzae & Fermentation. The author has an hindex of 45, co-authored 219 publications receiving 6419 citations. Previous affiliations of Rintu Banerjee include Indian Institutes of Technology & Sardar Patel University.
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Enzymatic transesterification of Jatropha oil
TL;DR: This is the first report on biodiesel synthesis using immobilized E. aerogenes lipase, and there was negligible loss in lipase activity even after repeated use for seven cycles.
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Seed birth to death: dual functions of reactive oxygen species in seed physiology
TL;DR: Knowing the mechanisms by which ROS influence seed physiology will provide insights that may not only allow the development of seed quality markers but also help to understand how dormancy can be broken in several recalcitrant species.
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Enrichment of phenolics and free radical scavenging property of wheat koji prepared with two filamentous fungi
TL;DR: It is demonstrated that fermented wheat grain is a better source of phytochemicals compared to non-fermented wheat, and different carbohydrate cleaving enzymes are responsible for the improvement ofphytochemical properties of fermented wheat.
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Sustainable green solvents and techniques for lipid extraction from microalgae: A review
S. P. Jeevan Kumar,S. P. Jeevan Kumar,Garlapati Vijay Kumar,Garlapati Vijay Kumar,Archana Dash,Peter Scholz,Rintu Banerjee +6 more
TL;DR: In this article, the authors focus on the prospects of green solvents and extraction techniques that could improve the commercial viability of biodiesel production, which is a serious concern for a sustainable economy where it has necessitated alternative renewable energy that can have the potential to meet the futuristic needs.
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Optimization of culture parameters for extracellular protease production from a newly isolated Pseudomonas sp. using response surface and artificial neural network models
TL;DR: In this article, a predictive model of the combined effects of independent variables (pH, temperature, inoculum volume) for extracellular protease production from a newly isolated Pseudomonas sp.