Abstract::
Plant tissue culture is a process of in-vitro regeneration requiring numerous resources and
intensive labour to mass produce disease-free clones. Diverse factors such as sterilizing agents, media
composition, and environmental conditions contribute toward successful regeneration and decide
the production, such as the total shoot number, shoot length, in vitro rooting, and adaptation of plants
to the external environment. Plant tissue culture, the successful induction of rapid shoot production,
and subsequent root formation in plants are influenced by the utilization of appropriate growing conditions
customized to each specific explant type. By carefully manipulating environmental factors,
such as temperature, light, and nutrient availability, it is possible to stimulate the growth and development
of new shoots in a time-efficient manner. This strategic combination of optimal growing
conditions and hormone supplementation holds great promise in the domain of efficient propagation
of plants through tissue culture techniques. The recent progress in artificial techniques such as artificial
neural networks (ANN) and machine learning (ML) algorithms has presented promising opportunities
for the development of sustainable and precise plant tissue culture processes. These techniques
are widely recognized as robust techniques for assessing outcomes and enhancing the accuracy
of predicting outputs in the domain of plant tissue culture. AI techniques and optimization algorithms
have been applied to predict and optimize callogenesis, embryogenesis, several shoots, shoot
length, hairy root culture, in vitro rooting, and plant acclimatization by helping predict sterilizing
conditions, optimal culture conditions, and formulation of a suitable medium. Patents, modeling, and
formulation of each stage of plant tissue culture using tools like artificial neural networks (ANNs),
neuro-fuzzy logic, support vector machines (SVMs), decision trees (DT), random forests (FR), and
genetic algorithms (GA) are presented.
Conclusion::
In this article, the current state of Artificial Intelligence (AI) algorithms, including their
applications in all elements of plant tissue culture, as well as the patents that have been gained for
these algorithms, are dissected in great detail