Low-cost media engineering for phosphate and IAA production by Kosakonia pseudosacchari TCPS-4 using Multi-objective Genetic Algorithm (MOGA) statistical tool.

The plant growth-promoting rhizobacteria (PGPR) can improve the biotic or abiotic stress condition by exploiting the productivity and plant growth of the plants under stressful conditions. This study examines the role of a rhizospheric bacterial isolate Kosakonia pseudosacchari TCPS-4 isolated from cluster bean plant (Cyamopsis tetragonoloba) under dryland condition. The low-cost media engineering was evaluated, and the phosphate-solubilizing and IAA-producing abilities of Kosakonia pseudosacchari TCPS-4 were improved using a hybrid statistical tool viz. Multi-objective Genetic Algorithm (MOGA). Further, the effect of carbon and nitrogen media constituents and their interactions on IAA production and phosphate solubilization were also confirmed by a single-factor experiment assay. This revealed that MOGA-based model depicted 47.5 mg/L inorganic phosphate as the highest phosphate concentration in media containing 45 g/L carbon source, 12 g/L nitrogen source and 0.20 g/L MgSO4. The highest IAA production was 18.74 mg/L in media containing 45 g/L carbon source, 12 g/L nitrogen source and 0.2 g/L MgSO4. These values were also confirmed and measured by the experiments with phosphate solubilization of 45.71 mg/L and IAA production of 18.71 mg/L with 1012 cfu/mL. This concludes that effective media engineering using these statistical tools can enhance the phosphate and IAA production by each model. A good correlation between measured and predicted values of each model confirms the validity of both responses. The present study gives an insight on media engineering for phosphate and IAA production by Kosakonia pseudosacchari TCPS-4.