Journal
BIOMOLECULES
Volume 10, Issue 5, Pages -Publisher
MDPI
DOI: 10.3390/biom10050746
Keywords
algorithms; artificial intelligence; auxins; cytokinins; in vitro culture; Kalanchoe; plant growth regulators (PGRs); plant tissue culture
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Funding
- Xunta de Galicia through Red de Uso Sostenible de los Recursos Naturales y Agroalimentarios (REDUSO) [ED431D 2017/18]
- Xunta de Galicia through Cluster of Agricultural Research and Development (CITACA Strategic Partnership) [ED431E 2018/07]
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Organogenesis constitutes the biological feature driving plant in vitro regeneration, in which the role of plant hormones is crucial. The use of machine learning (ML) technology stands out as a novel approach to characterize the combined role of two phytohormones, the auxin indoleacetic acid (IAA) and the cytokinin 6-benzylaminopurine (BAP), on the in vitro organogenesis of unexploited medicinal plants from the Bryophyllum subgenus. The predictive model generated by neurofuzzy logic, a combination of artificial neural networks (ANNs) and fuzzy logic algorithms, was able to reveal the critical factors affecting such multifactorial process over the experimental dataset collected. The rules obtained along with the model allowed to decipher that BAP had a pleiotropic effect on the Bryophyllum spp., as it caused different organogenetic responses depending on its concentration and the genotype, including direct and indirect shoot organogenesis and callus formation. On the contrary, IAA showed an inhibiting role, restricted to indirect shoot regeneration. In this work, neurofuzzy logic emerged as a cutting-edge method to characterize the mechanism of action of two phytohormones, leading to the optimization of plant tissue culture protocols with high large-scale biotechnological applicability.
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