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Efficiency of neural network-based combinatorial model predicting optimal culture conditions for maximum biomass yields in hairy root cultures.
MedLine Citation:
PMID:  23143691     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
KEY MESSAGE : ANN-based combinatorial model is proposed and its efficiency is assessed for the prediction of optimal culture conditions to achieve maximum productivity in a bioprocess in terms of high biomass. A neural network approach is utilized in combination with Hidden Markov concept to assess the optimal values of different environmental factors that result in maximum biomass productivity of cultured tissues after definite culture duration. Five hidden Markov models (HMMs) were derived for five test culture conditions, i.e. pH of liquid growth medium, volume of medium per culture vessel, sucrose concentration (%w/v) in growth medium, nitrate concentration (g/l) in the medium and finally the density of initial inoculum (g fresh weight) per culture vessel and their corresponding fresh weight biomass. The artificial neural network (ANN) model was represented as the function of these five Markov models, and the overall simulation of fresh weight biomass was done with this combinatorial ANN-HMM. The empirical results of Rauwolfia serpentina hairy roots were taken as model and compared with simulated results obtained from pure ANN and ANN-HMMs. The stochastic testing and Cronbach's α-value of pure and combinatorial model revealed more internal consistency and skewed character (0.4635) in histogram of ANN-HMM compared to pure ANN (0.3804). The simulated results for optimal conditions of maximum fresh weight production obtained from ANN-HMM and ANN model closely resemble the experimentally optimized culture conditions based on which highest fresh weight was obtained. However, only 2.99 % deviation from the experimental values could be observed in the values obtained from combinatorial model when compared to the pure ANN model (5.44 %). This comparison showed 45 % better potential of combinatorial model for the prediction of optimal culture conditions for the best growth of hairy root cultures.
Authors:
Shakti Mehrotra; O Prakash; Feroz Khan; A K Kukreja
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-11-11
Journal Detail:
Title:  Plant cell reports     Volume:  -     ISSN:  1432-203X     ISO Abbreviation:  Plant Cell Rep.     Publication Date:  2012 Nov 
Date Detail:
Created Date:  2012-11-12     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9880970     Medline TA:  Plant Cell Rep     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
Plant Biotechnology Division, Central Institute of Medicinal and Aromatic Plants, P.O. CIMAP, Picnic spot Road, Lucknow, India, shaktimehrotra22@gmail.com.
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