Modeling and Optimizing Medium Composition for Shoot Regeneration of Chrysanthemum via Radial Basis Function-Non-dominated Sorting Genetic Algorithm-II (RBF-NSGAII).
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
03 12 2019
03 12 2019
Historique:
received:
03
01
2019
accepted:
04
11
2019
entrez:
5
12
2019
pubmed:
5
12
2019
medline:
18
11
2020
Statut:
epublish
Résumé
The aim of the current study was modeling and optimizing medium compositions for shoot proliferation of chrysanthemum, as a case study, through radial basis function- non-dominated sorting genetic algorithm-II (RBF-NSGAII). RBF as one of the artificial neural networks (ANNs) was used for modeling four outputs including proliferation rate (PR), shoot number (SN), shoot length (SL), and basal callus weight (BCW) based on four variables including 6-benzylaminopurine (BAP), indole-3-butyric acid (IBA), phloroglucinol (PG), and sucrose. Afterward, models were linked to the optimization algorithm. Also, sensitivity analysis was applied for evaluating the importance of each input. The R
Identifiants
pubmed: 31796784
doi: 10.1038/s41598-019-54257-0
pii: 10.1038/s41598-019-54257-0
pmc: PMC6890634
doi:
Substances chimiques
Plant Growth Regulators
0
Sucrose
57-50-1
Phloroglucinol
DHD7FFG6YS
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
18237Références
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