A Cost-Effective Method for Identifying Nutrient Media Combinations Producing Plants with Maximum Bioactive Substances

Authors

  • Valeriya Simeonova Faculty of Mathematics and Informatics, Sofia University "St. Kliment Ohridski", Bulgaria
  • Krassimira Tasheva Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Bulgaria
  • Georgina Kosturkova Institute of Plant Physiology and Genetics, Bulgarian Academy of Sciences, Bulgaria
  • Dimitar Vassilev Faculty of Mathematics and Informatics, Sofia University "St. Kliment Ohridski", Bulgaria

DOI:

https://doi.org/10.55630/sjc.2018.12.191-218

Keywords:

Artificial Neural Networks, QSAR, Rhodiola Rosea, in vitro

Abstract

The aim is to find a cost-effective method of identifying nutrient media producing identical plants with maximum performance in terms of the bioactive substances contained in them. An adaptation of QSAR is used. The "spatial structure of the chemical component" is replaced with "the multidimensional structure of the nutrient medium" or with the treated day schemes. For each process, a separate forecast is made. All nutrition media produced in silico are based on the ranges of phytonutrient hormones in biotechnological experiments. We found 43 theoretical combinations of media with more than 80% success under conditions of limited resources in the price range of [0-1,5] euro/liter. The obtained results can be used as: a theoretical guideline for determining the optimal nutrient media and combinations; to the study of other medicinal plants in order to establish effective biotechnological schemes for growth and rooting that are also cost-effective; using ANN, taking into account the species and the ecotype.

Downloads

Published

2018-12-14

Issue

Section

Articles