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Genetic programming based models in plant tissue culture: An addendum to traditional statistical approach

In this paper, we compared the efficacy of observation based modeling approach using a genetic algorithm with the regular statistical analysis as an alternative methodology in plant research. Preliminary experimental data on in vitro rooting was taken for this study with an aim to understand the eff...

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Bibliographic Details
Published in:PLoS computational biology 2018-02, Vol.14 (2), p.e1005976-e1005976
Main Authors: Mridula, Meenu R, Nair, Ashalatha S, Kumar, K Satheesh
Format: Article
Language:English
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Summary:In this paper, we compared the efficacy of observation based modeling approach using a genetic algorithm with the regular statistical analysis as an alternative methodology in plant research. Preliminary experimental data on in vitro rooting was taken for this study with an aim to understand the effect of charcoal and naphthalene acetic acid (NAA) on successful rooting and also to optimize the two variables for maximum result. Observation-based modelling, as well as traditional approach, could identify NAA as a critical factor in rooting of the plantlets under the experimental conditions employed. Symbolic regression analysis using the software deployed here optimised the treatments studied and was successful in identifying the complex non-linear interaction among the variables, with minimalistic preliminary data. The presence of charcoal in the culture medium has a significant impact on root generation by reducing basal callus mass formation. Such an approach is advantageous for establishing in vitro culture protocols as these models will have significant potential for saving time and expenditure in plant tissue culture laboratories, and it further reduces the need for specialised background.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1005976