Kusum Arunachalam

Isolation and evaluation of cultivation conditions of Euglena sp. from Western Himalaya for biofuel production

ABSTRACT This study aims to isolate the unicellular green alga Euglena sp. from wastewater collected from river Rispana of Dehradun, Uttarakhand, India. The optimization of different environmental factors for biomass production was performed. The physico-chemical factors significantly affect the culture growth and biomass of the microalga, and therefore optimization of these parameters is important for the commercialization of microalgae based biofuels. In this research, the collective effect of media composition, light intensity, photoperiod, temperature and pH was studied on the biomass of the isolated strain. The maximum biomass (0.838 g L−1) was obtained in the blue-green (BG-11) medium under a light intensity of 120 µmol m−2 sec−1 and a 16:8 light: dark cycle at 25°C. The life cycle of Euglena sp. was also assessed. The life cycle of the Euglena sp. varied from 12 to 20 days but after the 10th day the culture undergoes the stationary phase of the life cycle. Euglena sp. may be evaluated for its potential as a biofuel feed stock.

Modeling Euglena sp. growth under different conditions using an artificial neural network

Microalgae are considered as the future source of biofuels because of their high biomass productivity and neutral lipid content as triacylglycerides (TAG). Microalgae have high photosynthetic efficiency and the possibility of being cultivated in different wastewaters. The isolation of potential microalgae followed by the optimization of cultivation conditions is prerequisite for successful cultivation and accumulation of high lipid content. In the present work, a three-layer artificial neural network (ANN) model is developed to predict the essential parameters (such as pH, temperature, light intensity, photoperiod, and medium composition) based on 156 sets of laboratory experiments for achieving maximum biomass from Euglena sp. The independent parameters (viz., temperature, light intensity, photoperiod and number of days at fixed pH, and media composition) were fed as input to the ANN, and biomass yield was investigated. The comparison of the simulated environmental conditions using the ANN model and experimental results are found to have an excellent correlation coefficient of about 0.97 for the model variables used in this study. The model results established that artificial neural network design may be judiciously employed for optimization of different environmental conditions for this isolated microalga.

Distribution, ecophysiology and medicinal and nutraceutical usage of Perilla frutescens (L.) Britton

Perilla frutescens is one of the important crops grown in Garhwal and Kumaon hills of Uttarakhand, India. Traditionally the seeds of the plant are eaten raw by people and oil extracted from seeds are used for cooking purposes. Medicinally, it is used in treating cough, bronchitis, uterine ailments and rheumatic arthritis. Most of the research on P. frutescens in India in general and Uttarakhand in particular have focused on characterization of its chemical constituents, genetic relationship between the wild and cultivated variety, its uses, and how cultivation practices have changed over the years. Here we envisaged on the R&D gaps for comprehensive understanding of its formulations as health food and nutraceuticals.