Neural modeling of plant tissue cultures: a review

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.