title: Artificial neural network-based model for the prediction of optimal growth and culture conditions for maximum biomass accumulation in multiple shoot cultures of Centella asiatica.
abstract: An artificial neural network (ANN)-based modelling approach is used to determine the synergistic effect of five major components of growth medium (Mg, Cu, Zn, nitrate and sucrose) on improved in vitro biomass yield in multiple shoot cultures of Centella asiatica. The back propagation neural network (BPNN) was employed to predict optimal biomass accumulation in terms of growth index over a defined culture duration of 35 days. The four variable concentrations of five media components, i.e. MgSO4(0, 0.75, 1.5, 3.0 mM), ZnSO4(0, 15, 30, 60 μM), CuSO4(0, 0.05, 0.1, 0.2 μM), NO3(20, 30, 40, 60 mM) and sucrose (1, 3, 5, 7 %, w/v) were taken as inputs for the ANN model. The designed model was evaluated by performing three different sets of validation experiments that indicated a greater similarity between the target and predicted dataset. The results of the modelling experiment suggested that 1.5 mM Mg, 30 μM Zn, 0.1 μM Cu, 40 mM NO3and 6 % (w/v) sucrose were the respective optimal concentrations of the tested medium components for achieving maximum growth index of 1654.46 with high centelloside yield (62.37 mg DW/culture) in the cultured multiple shoots. This study can facilitate the generation of higher biomass of uniform, clean, good quality C. asiatica herb that can efficiently be utilized by pharmaceutical industries.
authors.affiliation: Division of Plant Biotechnology, CSIR-Central Institute of Medicinal & Aromatic Plants (CSIR-CIMAP); PO CIMAP, Lucknow, 226015, India.
authors.forename: Archana
authors.initials: A
authors.lastname: Prasad
authors.affiliation: Division of Molecular and Structural Biology, CSIR-Central Institute of Medicinal & Aromatic Plants (CSIR-CIMAP); PO CIMAP, Lucknow, 226015, India.
authors.forename: Om
authors.initials: O
authors.lastname: Prakash
authors.affiliation: Division of Plant Biotechnology, CSIR-Central Institute of Medicinal & Aromatic Plants (CSIR-CIMAP); PO CIMAP, Lucknow, 226015, India.
authors.forename: Shakti
authors.initials: S
authors.lastname: Mehrotra
authors.affiliation: Division of Molecular and Structural Biology, CSIR-Central Institute of Medicinal & Aromatic Plants (CSIR-CIMAP); PO CIMAP, Lucknow, 226015, India.
authors.forename: Feroz
authors.initials: F
authors.lastname: Khan
authors.affiliation: Division of Plant Biotechnology, CSIR-Central Institute of Medicinal & Aromatic Plants (CSIR-CIMAP); PO CIMAP, Lucknow, 226015, India.
authors.forename: Ajay Kumar
authors.initials: AK
authors.lastname: Mathur
authors.affiliation: Division of Plant Biotechnology, CSIR-Central Institute of Medicinal & Aromatic Plants (CSIR-CIMAP); PO CIMAP, Lucknow, 226015, India. archnacimap@gmail.com.
authors.forename: Archana
authors.initials: A
authors.lastname: Mathur
mesh_terms: D018533:Biomass; D028041:Centella / Q000254:growth & development*; D008954:Models, Biological; D016571:Neural Networks, Computer; D018520:Plant Shoots / Q000254:growth & development*; D012044:Regression Analysis; D015203:Reproducibility of Results; D046509:Tissue Culture Techniques / Q000379:methods*
keywords: Artificial neural network modelling; Centella asiatica; Media optimization; Multiple shoot cultures