Modeling tool using neural networks for l(+)-lactic acid production by pellet-form Rhizopus oryzae NRRL 395 on biodiesel crude glycerol

被引:9
作者
Dulf, Eva-H. [1 ]
Vodnar, Dan Cristian [2 ]
Dulf, Francisc-V. [3 ]
机构
[1] Tech Univ Cluj Napoca, Automat Dept, Cluj Napoca, Romania
[2] Univ Agr Sci & Vet Med Cluj Napoca, Dept Food Sci & Technol, Cluj Napoca, Romania
[3] Univ Agr Sci & Vet Med Cluj Napoca, Dept Environm & Plant Protect, Cluj Napoca, Romania
关键词
Software application; Neural network; Biodiesel; Predictive model;
D O I
10.1186/s13065-018-0491-5
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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.
引用
收藏
页数:9
相关论文
共 13 条
[1]   Artificial neural network modeling of p-cresol photodegradation [J].
Abdollahi, Yadollah ;
Zakaria, Azmi ;
Abbasiyannejad, Mina ;
Masoumi, Hamid Reza Fard ;
Moghaddam, Mansour Ghaffari ;
Matori, Khamirul Amin ;
Jahangirian, Hossein ;
Keshavarzi, Ashkan .
CHEMISTRY CENTRAL JOURNAL, 2013, 7
[2]  
[Anonymous], 2016, DEEP LEARNING
[3]  
Comert Z., 2017, J Sci Technol, V7, P93, DOI [10.17678/beuscitech.338085, DOI 10.17678/BEUSCITECH.338085]
[4]   Challenges and opportunities in lactic acid bioprocess design-From economic to production aspects [J].
de Oliveira, Regiane Alves ;
Komesu, Andrea ;
Vaz Rossell, Carlos Eduardo ;
Maciel Filho, Rubens .
BIOCHEMICAL ENGINEERING JOURNAL, 2018, 133 :219-239
[5]   Phenolic compounds, flavonoids, lipids and antioxidant potential of apricot (Prunus armeniaca L.) pomace fermented by two filamentous fungal strains in solid state system [J].
Dulf, Francisc Vasile ;
Vodnar, Dan Cristian ;
Dulf, Eva-Henrietta ;
Pintea, Adela .
CHEMISTRY CENTRAL JOURNAL, 2017, 11
[6]   Production of L-lactic acid by the yeast Candida sonorensis expressing heterologous bacterial and fungal lactate dehydrogenases [J].
Ilmen, Marja ;
Koivuranta, Kari ;
Ruohonen, Laura ;
Rajgarhia, Vineet ;
Suominen, Pirkko ;
Penttila, Merja .
MICROBIAL CELL FACTORIES, 2013, 12
[7]   Recent developments and key barriers to advanced biofuels: A short review [J].
Oh, You-Kwan ;
Hwang, Kyung-Ran ;
Kim, Changman ;
Kim, Jung Rae ;
Lee, Jin-Suk .
BIORESOURCE TECHNOLOGY, 2018, 257 :320-333
[8]  
Pradima J., 2017, RES EFF TECHN, V3, P394, DOI DOI 10.1016/J.REFFIT.2017.02.009
[9]   Genome scale metabolic models as tools for drug design and personalized medicine [J].
Raskevicius, Vytautas ;
Mikalayeva, Valeryia ;
Antanaviciute, Ieva ;
Cesleviciene, Ieva ;
Skeberdis, Vytenis Arvydas ;
Kairys, Visvaldas ;
Bordel, Sergio .
PLOS ONE, 2018, 13 (01)
[10]   Application of an artificial neural network model for the supercritical fluid extraction of seed oil from Argemone mexicana (L.) seeds [J].
Suryawanshi, Bhupendra ;
Mohanty, Bikash .
INDUSTRIAL CROPS AND PRODUCTS, 2018, 123 :64-74