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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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Published in: | PLoS computational biology 2018-02, Vol.14 (2), p.e1005976-e1005976 |
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description | 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. |
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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.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1005976</identifier><identifier>PMID: 29485995</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Acetic acid ; Biology and Life Sciences ; Biotechnology ; Callus ; Charcoal ; Computer and Information Sciences ; Expenditures ; Experiments ; Genetic algorithms ; Genetic analysis ; Genetic aspects ; Genetic engineering ; Growth models ; Laboratories ; Mathematical models ; Naphthalene ; Physical Sciences ; Plant tissue culture ; Plant tissues ; Plantlets ; Problem solving ; Regression analysis ; Research and Analysis Methods ; Scholarships & fellowships ; Software ; Statistical analysis ; Statistics ; Tissue culture ; Variables ; Variance analysis</subject><ispartof>PLoS computational biology, 2018-02, Vol.14 (2), p.e1005976-e1005976</ispartof><rights>COPYRIGHT 2018 Public Library of Science</rights><rights>2018 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Mridula MR, Nair AS, Kumar KS (2018) Genetic programming based models in plant tissue culture: An addendum to traditional statistical approach. PLoS Comput Biol 14(2): e1005976. https://doi.org/10.1371/journal.pcbi.1005976</rights><rights>2018 Mridula et al 2018 Mridula et al</rights><rights>2018 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Mridula MR, Nair AS, Kumar KS (2018) Genetic programming based models in plant tissue culture: An addendum to traditional statistical approach. 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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.</description><subject>Acetic acid</subject><subject>Biology and Life Sciences</subject><subject>Biotechnology</subject><subject>Callus</subject><subject>Charcoal</subject><subject>Computer and Information Sciences</subject><subject>Expenditures</subject><subject>Experiments</subject><subject>Genetic algorithms</subject><subject>Genetic analysis</subject><subject>Genetic aspects</subject><subject>Genetic engineering</subject><subject>Growth models</subject><subject>Laboratories</subject><subject>Mathematical models</subject><subject>Naphthalene</subject><subject>Physical Sciences</subject><subject>Plant tissue culture</subject><subject>Plant tissues</subject><subject>Plantlets</subject><subject>Problem 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Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mridula, Meenu R</au><au>Nair, Ashalatha S</au><au>Kumar, K Satheesh</au><au>Durand, Jean-Baptiste</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genetic programming based models in plant tissue culture: An addendum to traditional statistical approach</atitle><jtitle>PLoS computational biology</jtitle><addtitle>PLoS Comput Biol</addtitle><date>2018-02-01</date><risdate>2018</risdate><volume>14</volume><issue>2</issue><spage>e1005976</spage><epage>e1005976</epage><pages>e1005976-e1005976</pages><issn>1553-7358</issn><issn>1553-734X</issn><eissn>1553-7358</eissn><abstract>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. 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subjects | Acetic acid Biology and Life Sciences Biotechnology Callus Charcoal Computer and Information Sciences Expenditures Experiments Genetic algorithms Genetic analysis Genetic aspects Genetic engineering Growth models Laboratories Mathematical models Naphthalene Physical Sciences Plant tissue culture Plant tissues Plantlets Problem solving Regression analysis Research and Analysis Methods Scholarships & fellowships Software Statistical analysis Statistics Tissue culture Variables Variance analysis |
title | Genetic programming based models in plant tissue culture: An addendum to traditional statistical approach |
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