Browsing by Author "Kumar, Ashwani"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Characterization of CLA-producing Butyrivibrio spp. reveals strain-specific variations
    (3 Biotech, 2016) Kumar, Ashwani
    Conjugated Linoleic Acid (CLA), a fatty acid with high nutraceutical value is produced in rumen by resident bacterial species, especially Butyrivibrio spp. The present study was undertaken to examine the diversity of indigenous Butyrivibrio spp. from rumen liquor of Indian ruminants. The isolates were screened for their CLA production capability at different level of linoleic acid (LA) (0, 200, 400, 600, 800 lg/ml) at different time intervals (0, 2, 4, 6, 12, and 24 h). A total of more than 300 anaerobic cultures were isolated and 31 of them were identified as Butyrivibrio spp. based on morphological, biochemical and molecular characterization. Further, molecular characterization revealed that a large portion (67.7 %) of isolated Butyrivibrio belonged to Butyrivibrio fibrisolvens (B. fibrisolvens) species which is considered to be the most active bacteria amongst the rumen bacteria populace in terms of CLA production. Bacterial isolate VIII (strain 4a) showed highest CLA production ability (140.77 lg/ml) when incubated at 200 lg/ml LA for 2 h, which is 240 % higher than the isolate XXVII, Butyrivibrio proteoclasticus (B. proteoclasticus) showing lowest CLA production (57.28 lg/ml) amongst the screened isolates. It was evident from the observations recorded during the course of experiments that CLA production ability is strain specific and thus did not follow a single pattern. CLA production also varied with time of incubation and concentration of free linoleic acid supplemented in the growth medium. The results of these findings put forward a strain that is high CLA producer and can be further exploited as an additive for enhancing meat and milk quality in ruminants
  • Thumbnail Image
    Item
    Improved pullulan production and process optimization using novel GA–ANN and GA–ANFIS hybrid statistical tools
    (Biomolecules, 2020) Budhwar, Parul; Kumar, Ashwani; Yadav, Ankush; Kumar, Punit; Siwach, Ritu; Chabra, Deepak; Dubey, Kashyap.Kumar
    Pullulan production from Aureobasidium pullulans was explored to increase yield. Non-linear hybrid mathematical tools for optimization of process variables as well as the pullulan yield were analyzed. The one variable at a time (OVAT) approach was used to optimize the maximum pullulan yield of 35.16 0.29 g/L. The tools predicted maximum pullulan yields of 39.4918 g/L (genetic algorithm coupled with artificial neural network (GA–ANN)) and 36.0788 g/L (GA coupled with adaptive network based fuzzy inference system (GA–ANFIS)). The best regression value (0.94799) of the Levenberg–Marquardt (LM) algorithm forANNand the epoch error (6.1055 10􀀀5) for GA–ANFIS point towards prediction precision and potentiality of data training models. The process parameters provided by both the tools corresponding to their predicted yield were revalidated by experiments. Among the two of them GA–ANFIS results were replicated with 98.82% accuracy. Thus GA–ANFIS predicted an optimum pullulan yield of 36.0788 g/L with a substrate concentration of 49.94 g/L, incubation period of 182.39 h, temperature of 27.41 C, pH of 6.99, and agitation speed of 190.08 rpm.
  • Thumbnail Image
    Item
    Microbial alkaline proteases: Optimization of production parameters and their properties
    (Journal of Genetic Engineering and Biotechnology, 2017) Kumar, Ashwani