ArticleChemistry Central journal2018
Modeling tool using neural networks for L(+)-lactic acid production by pellet-form Rhizopus oryzae NRRL 395 on biodiesel crude glycerol.
Article in Chemistry Central journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Lactic acid fermentation using Rhizopus spp.: current insights and future prospects.Bioresources and bioprocessing · 2025Review
- Mathematical Modeling and Optimization ofFrontiers in bioengineering and biotechnology · 2022Article
- Biomass-Derived Production of Itaconic Acid as a Building Block in Specialty Polymers.Polymers · 2019Review
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Authors and funding
3 authors.
Funding
Abstract
Most chemical reactions produce unwanted by-products. In an effort to reduce environmental problems these by-products could be used to produce valuable organic chemicals. In biodiesel industry a huge amount of glycerol is generated, approximately 10% of the final product. The research group from University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca developed opportunities to produce L(+) lactic acid from the glycerol. The team is using the Rhizopus oryzae NRRL 395 bacteria for the fermentation of the glycerol. The purpose of the research is to improve the production of L(+) lactic acid in order to optimize the process. A predictive model obtained by neural networks is useful in this case. The main objective of the present work is to present the developed user-friendly application useful in modeling this fermentation process, in order to be used by people who are inexperienced with neural networks or specific software. Besides the interface for training of a new neural network in order to develop the model in some characteristic condition, the software also provides an interface for visualization of the results, useful in interpretation and as a tool for prediction.
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