Centella asiatica, a weakly aromatic plant that flourishes in wet tropical and sub-tropical areas as
a medicinal species since ancient times. It contained important terpenoids that impart important
medicinal values. Currently, studies on the terpenoid content of various Centella asiatica
phenotypes have shown not only variable content but variable growth rates of different
phenotypes that can affect future selection of phenotypes. The use of mathematical growth
modelling can reveal important growth constants and discriminate between faster and slower
growth phenotypes. Two Centella asiatica phenotypes from South Africa is modelled using the
modified Gompertz model and the results showed that the C. asiatica Type-1 exhibited a faster
growth rates and a shorter lag period at 0.152 day-1 and 2.313 day than another phenotype; C.
asiatica Type 2 with a growth rate and a lag period of 0.067 day-1 and 3.363 day, respectively.
The data indicates that different phenotypes of C. asiatica can have different growth rates and
lag period and this can be important for selection of phenotypes to be used as the best bioactive
peptides producer.
One of the most important preliminary investigation of callus attributes is the growth
characteristics. Most often than not, callus growth curve is sigmoidal in characteristics. In this
work, we model callus growth from the seedling of Jatropha curcas L. according to the
modified Gompertz model from published literature to acquire essential growth constants.
These growth constants can be obtained with better precision using model such as the modified
Gompertz. Parameters obtained from the fitting exercise were maximum callus growth rate
(μm), lag time (l) and maximal callus production (Ymax) of 0.193 d-1, 2.91 days and 0.38 g
callus/25 mL culture, respectively. Growth parameter constants extracted from the modelling
exercise will be helpful for additional secondary modelling implicating the consequence of
media conditions as well as other factors on the growth of callus from this plant.
The mistletoe fig (Ficus deltoidea) is frequently found in several areas of the world, and primarily functions as houseplant or an ornamental shrub. The plant is discovered indigenous generally in Asia tropical region for example Indonesia, Philippines, Malaysia, and Thailand. Scientific studies on the effect of plant growth regulators on cells production from this plant are vital as optimization of cells production may result in effective production of secondary products characterization and output. The growth of cell suspension cultures from this plant shows sigmoidal property. In this work, we model the effect of the plant growth regulator 2,4-dichlorophenoxyacetic acid (2,4-D) on the growth kinetics of the cells from this plant according to the modified Gompertz model. The coefficient of determination showed good agreement between experimental and predicted data with values ranging from 0.97-0.98. The results showed that 2,4-D at 2 mg/L was optimal for achieving the highest cells growth rate. It is anticipated that the growth parameter constants extracted from the modelling exercise will be helpful in the future for additional secondary modelling on the effect of media conditions as well as other factors on cells growth.
Ficus deltoidea (or commonly known as mistletoe fig) in various parts of the world mainly
serves as an ornamental shrub or houseplant and found native mainly in Asia tropical region,
for example, Malaysia, Indonesia, Philippines and Thailand. Studies on the effect of plant
growth regulators on cells production from this plant is important as optimization of cells
production can lead to efficient production of secondary products characterization and
production. An important aspect of the sigmoidal cells growth curve is the growth parameters.
In this work, we model the effect of picloram (4-amino-3,5,6-trichloropicolinic acid) on the
growth kinetics of the cell suspension cultures of Ficus deltoidea according to the modified
Gompertz model. The adjusted coefficient of determination showed good agreement between
experimental and predicted data with values ranging from 0.97-0.99. Parameters obtained from
the fitting exercise were maximum cells growth rate (μm), lag time (l) and maximal cells
production (Ymax). The results showed that picloram at concentrations of 3 mg/L and above
were optimal for giving the highest cells growth rate measured as PCV (packed cell volume).
The parameter growth rate obtained from the modelling exercise will be helpful for additional
secondary modelling implicating the consequence of media conditions as well as other factors
on the effect of picloram on the growth rate of cell suspension from this plant.