Isolation, Optimization And Characterization Of Amylase-Producing Rhizospheric Bacteria For Agro-Industrial Waste Valorization

Abstract

Agro-industrial processing generates large volumes of starch-rich residues that are frequently discarded despite their potential
as renewable bioconversion resources. The present study investigated the isolation, screening, characterization, and
optimization of amylase-producing microorganisms obtained from rhizospheric soils and evaluated their applicability in the
bioconversion of agro-industrial waste. Rhizospheric soil samples collected from Harij, Palanpur, Patan, and Banaskantha
regions yielded twenty bacterial isolates, among which ten demonstrated amylase-producing capability based on starch
hydrolysis assays. Hydrolysis capacity values varied between 20.4 and 37.8, with isolate A6 showing the highest plate-based
hydrolysis efficiency. Four promising isolates (A3, A4, A6, and A9) were selected for further characterization based on their
enzymatic potential. Morphological and cultural analysis revealed diversity in colony size, pigmentation, and structural
features, suggesting variation in metabolic capabilities among isolates. Submerged fermentation studies demonstrated
significant differences in extracellular amylase production, with isolate A9 exhibiting the highest enzyme activity of
approximately 275 U/ml, indicating superior secretion efficiency. Optimization of fermentation parameters including pH,
temperature, incubation time, and inoculum size resulted in progressive enhancement of enzyme yield, reaching approximately
380 U/ml under optimized conditions. The study also confirmed that pretreatment of agro-industrial substrates through
gelatinization significantly improved starch accessibility and sugar release during enzymatic hydrolysis.
Statistical optimization using Response Surface Methodology indicated that wheat bran concentration had a major influence
on enzyme production, whereas yeast extract exhibited moderate impact and starch concentration showed comparatively
minimal contribution within the tested range. Significant quadratic effects were observed for all variables, confirming the
presence of optimal nutrient concentrations necessary for maximum enzyme synthesis. The developed model showed high
reliability with a statistically significant regression and non-significant lack-of-fit, demonstrating accurate prediction
capability.
Overall, the findings highlight rhizospheric soil as a rich reservoir of efficient amylase-producing bacteria and confirm the
potential of microbial amylase in sustainable agro-industrial waste valorization. The optimized fermentation strategy
demonstrated in this study provides a cost-effective and environmentally friendly approach for producing industrially relevant
enzymes and converting starch-based residues into valuable biochemical products.