Artificial neural networks modeling the in vitro rhizogenesis and acclimatization of Vitis vinifera L.
This study employs artificial neural networks (ANNs) to create a model to identify relationships between variables affecting the in vitro rhizogenesis and acclimatization of two cultivars of Vitis vinifera L. Albariño and Mencía. The effects of three factors (inputs), the type of cultivar, concentration and exposure time to indolebutyric acid (IBA), on the success of in vitro rhizogenesis and acclimatization were evaluated. The developed model, using ANNs software, was assessed using a separate set of validation data and was in good agreement with the observed results. Exposure time to IBA was found to have the dominant role in influencing the height of acclimatized plantlets. ANNs can be a useful tool for modeling different complex processes and data sets, in plant tissue cultures or, more generally, in plant biology.
Gago
Jorge
J
Applied Plant and Soil Biology, Faculty of Biology, University of Vigo, 36310 Vigo, Spain.
Landín
Mariana
M
Gallego
Pedro Pablo
PP
D000064:Acclimatization / Q000502:physiology*; D008954:Models, Biological; D016571:Neural Networks, Computer; D038081:Organogenesis / Q000502:physiology*; D018517:Plant Roots / Q000254:growth & development*; D015203:Reproducibility of Results; D012984:Software; D027843:Vitis / Q000254:growth & development*