REVIEW PAPER
Neural modeling of plant tissue cultures: a review
Publication date: 2014-10-23
BioTechnologia 2013;94(3):253-268
KEYWORDS
biomass estimationembryo classificationneural modelingplant clusteringprediction of conditionstissue culture
ABSTRACT
Artificial neural networks (ANNs) are widely used in science and technology, and have been successfully applied
in plant tissue cultures. First of all, ANNs can simulate the growth of plants under different in vitro conditions.
Their usefulness has been confirmed in the estimation of biomass in plant cell cultures and the length of shoots
in vitro, in the classification of somatic embryos, evaluation of the physical conditions of an in vitro environment,
and in the prediction of optimal conditions for in vitro culture to achieve maximum efficiency and productivity.
Secondly, with the help of various types of neural models, in vitro -regenerated plants are sorted, respectively,
to their quality and likeliness of further development. Thirdly, ANNs are capable of predicting plant behavior
during in vitro rhizogenesis and subsequent acclimatization to ex vitro conditions. Several neural and neurofuzzy
models for the aforementioned biological processes are reviewed in this paper. In addition, the fundamentals of
neural modeling, namely the construction of ANNs, are presented and their flexibility and attractiveness are
highlighted.
in plant tissue cultures. First of all, ANNs can simulate the growth of plants under different in vitro conditions.
Their usefulness has been confirmed in the estimation of biomass in plant cell cultures and the length of shoots
in vitro, in the classification of somatic embryos, evaluation of the physical conditions of an in vitro environment,
and in the prediction of optimal conditions for in vitro culture to achieve maximum efficiency and productivity.
Secondly, with the help of various types of neural models, in vitro -regenerated plants are sorted, respectively,
to their quality and likeliness of further development. Thirdly, ANNs are capable of predicting plant behavior
during in vitro rhizogenesis and subsequent acclimatization to ex vitro conditions. Several neural and neurofuzzy
models for the aforementioned biological processes are reviewed in this paper. In addition, the fundamentals of
neural modeling, namely the construction of ANNs, are presented and their flexibility and attractiveness are
highlighted.
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