Response surface methodology (RSM) was used to optimize the cultivation conditions for the production of phytase by recombinant Escherichia coli DH5α. The optimum predicted cultivation conditions for phytase production were at 3 hours seed age, a 2.5% inoculum level, an L-arabinose concentration of 0.20%, a cell concentration of 0.3 (as measured at 600 nm) and 17 hours post-induction time with a predicted phytase activity of 4194.45 U/mL. The model was validated and the results showed no significant difference between the experimental and the predicted phytase activity (P = 0.305). Under optimum cultivation conditions, the phytase activity of the recombinant E. coli DH5α was 364 times higher compared to the phytase activity of the wild-type producer, Enterobacter sakazakii ASUIA279. Hence, optimization of the cultivation conditions using RSM positively increased phytase production from recombinant E. coli DH5α.
Currently, the available indices to measure mangrove health are not comprehensive. An integrative ecological-socio economic index could give a better picture of the mangrove ecosystem health. This method explored all key biological, hydrological, ecological and socio-economic variables to form a comprehensive mangrove quality index. A total of 10 out of 43 variables were selected based on principal component analysis (PCA). They are aboveground biomass, crab abundance, soil carbon, soil nitrogen, number of phytoplankton species, number of diatom species, dissolved oxygen, turbidity, education level and fishing time spent by fishers. Two types of indices were successfully developed to indicate the health status viz., (1) Mangrove quality index for a specific category (MQISi ) and, (2) Overall mangrove quality index (MQI) to reflect the overall health status of the ecosystem. The indices for the five different categories were mangrove biotic integrity index ( M Q I S 1 ), mangrove soil index ( M Q I S 2 ), marine-mangrove index ( M Q I S 3 ), mangrove-hydrology index ( M Q I S 4 ) and mangrove socio-economic index ( M Q I S 5 ). The quality of the mangroves was classified from 1 to 5 viz. 1 (worst), 2 (bad), 3 (moderate), 4 (good), 5 (excellent). These MQI class could reflect the quality of mangrove forest which could be managed with the objective of improving its quality. Advantages of this method include: •PCA to select metrics from ecological-socioeconomic variables•Formulation of MQI based on selected metrics•Comprehensive index to classify mangrove ecosystem health.