Combined ANN/EVOP Factorial Design Approach for Media Screening for Cost-effective Production of Alkaline Proteases from Rhizopus oryzae (SN5)/NCIM-1447 under SSF

Abstract

Abstract In order to achieve high yield of fungal protease in a very cost effective way and to meet its increased market demand, current study deals with the screening of various agro-wastes as carbon source for the production of protease from Rhizopus oryzae (SN5)/NCIM-1447 under solid state fermentation. Substrates and culture parameters such as wheat bran, soybean meal, black-gram husk, rice husk, mixture of wheat bran, soybean meal, nitrogen sources, pH, temperature and incubation time were first optimized with one factor at time strategy and then EVOP factorial and yield of alkaline protease was achieved 412.8 U/gds at 28 °C and pH = 6 after 72 h of fermentation taking wheat bran and soybean as a substrate in 4:1 ratio. Further artificial neural networks (ANN), was trained with data of EVOP and yield of protease was enhanced up to 422.6 U/gds with wheat bran: soyabean in ratio of 70:30, pH 6.2 at 30 °C. The evolved process and Rhizopus oryzae (SN5)/NCIM-1447 strain would be promising for protease production at industrial scale at low cost.

Keywords

• Rhizopus oryzae
• EVOP
• Artificial neural networks (ANN)
• Alkaline protease
• Wheat bran