title: Statistical optimization of process variables for the large-scale production of Metarhizium anisopliae conidiospores in solid-state fermentation.
abstract: Optimization of conidial production was achieved by response surface methodology (RSM), a powerful mathematical approach widely applied in the optimization of fermentation process, using the three substrates; rice, barley and sorghum at variable pH, moisture content and yeast extract concentrations. These three factors were found to be important, affecting Metarhizium anisopliae spore production. A 2(3) full factorial central composite design and RSM were applied to determine the optimal concentration of each variable. A second-order polynomial was determined by the multiple regression analysis of the experimental data. Moisture content of 75.68% for sorghum, 73.21% for barley and 22.34% for rice produced optimal results. Maximal conidial yield was recorded for rice at a pH of 7.01; at 7.06 for sorghum and at 6.76 for barley.
authors.affiliation: Department of Botany, Andhra University, Visakhapatnam 530 003, Andhra Pradesh, India.
authors.forename: G V S
authors.initials: GV
authors.lastname: Bhanu Prakash
authors.forename: V
authors.initials: V
authors.lastname: Padmaja
authors.forename: R R
authors.initials: RR
authors.lastname: Siva Kiran
mesh_terms: D001230:Aspergillus / Q000378:metabolism; D019149:Bioreactors; D001709:Biotechnology / Q000295:instrumentation / Q000379:methods*; D005285:Fermentation; D001467:Hordeum; D006863:Hydrogen-Ion Concentration; D007218:Industrial Microbiology; D052981:Metarhizium / Q000378:metabolism*; D008962:Models, Theoretical; D012275:Oryza; D012044:Regression Analysis; D015203:Reproducibility of Results; D045868:Sorghum