Choosing an appropriate somatic embryogenesis medium of carrot (Daucus carota L.) by data mining technology.
Artificial neural network
Genetic algorithm
In vitro culture
Machine learning
Multilayer perceptron
Radial basis function
Journal
BMC biotechnology
ISSN: 1472-6750
Titre abrégé: BMC Biotechnol
Pays: England
ID NLM: 101088663
Informations de publication
Date de publication:
27 Sep 2024
27 Sep 2024
Historique:
received:
23
12
2023
accepted:
13
09
2024
medline:
28
9
2024
pubmed:
28
9
2024
entrez:
28
9
2024
Statut:
epublish
Résumé
Developing somatic embryogenesis is one of the main steps in successful in vitro propagation and gene transformation in the carrot. However, somatic embryogenesis is influenced by different intrinsic (genetics, genotype, and explant) and extrinsic (e.g., plant growth regulators (PGRs), medium composition, and gelling agent) factors which cause challenges in developing the somatic embryogenesis protocol. Therefore, optimizing somatic embryogenesis is a tedious, time-consuming, and costly process. Novel data mining approaches through a hybrid of artificial neural networks (ANNs) and optimization algorithms can facilitate modeling and optimizing in vitro culture processes and thereby reduce large experimental treatments and combinations. Carrot is a model plant in genetic engineering works and recombinant drugs, and therefore it is an important plant in research works. Also, in this research, for the first time, embryogenesis in carrot (Daucus carota L.) using Genetic algorithm (GA) and data mining technology has been reviewed and analyzed. In the current study, data mining approach through multilayer perceptron (MLP) and radial basis function (RBF) as two well-known ANNs were employed to model and predict embryogenic callus production in carrot based on eight input variables including carrot cultivars, agar, magnesium sulfate (MgSO The results showed that RBF had better prediction efficiency than MLP. Then, the developed model was linked to a genetic algorithm (GA) to optimize the system. To confirm the reliability and accuracy of the developed model, the result of RBF-GA was experimentally tested in the lab as a validation experiment. The result showed that there was no significant difference between the predicted optimized result and the experimental result. Generally, the results of this study suggest that data mining through RBF-GA can be considered as a robust approach, besides experimental methods, to model and optimize in vitro culture systems. According to the RBF-GA result, the highest somatic embryogenesis rate (62.5%) can be obtained from Nantes improved cultivar cultured on medium containing 195.23 mg/l MgSO
Identifiants
pubmed: 39334143
doi: 10.1186/s12896-024-00898-7
pii: 10.1186/s12896-024-00898-7
doi:
Substances chimiques
Culture Media
0
Plant Growth Regulators
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
68Informations de copyright
© 2024. The Author(s).
Références
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