Modeling of in Vitro Biomass Production of Digitalis purpurea Under the Effects of Biosynthetic Silver Nanoparticles

Abstract

Nanoparticles are being used in many areas in biotechnology. Silver nanoparticles are the most frequently used ones among the others, because of their eco-friendly natures. Biosynthetic silver nanoparticles have some beneficial effects on plant tissue cultures. However, their effects have rarely been investigated. In this study, biosynthetic nanoparticles were used at 0, 1, 2 and 4 mg/L concentration in order to determine their effects on Digitalis purpurea node cultures. At the first stage of experimental data analyses, MANOVA was employed to understand the significant growth parameters of D. purpurea plantlets. At the second stage, an artifical neural network (ANN) model was designed and tested under a wide range of input parameters (concentration of silver nanoparticles). The statistical differences between shoot elongations, single and multiple shoot formations, root formations, root fresh and dry weights were not found significant. However, the difference between shoot and total fresh weights, shoot and total dry weights (the significant variables) were found statistically significant. Optimum silver nanoparticle concentration for plantlet growth was detected as 2 mg/L. Biomass accumulations were enhanced up to 2,4 times. The results showed that ANN model provided a good prediction for the plant growth parameters and can be adapted for in vitro large-scale production.