Enhancing bioremediation research with mixed-effects models: A statistical approach to enzyme kinetics analysis

Bioremediation of petroleum-contaminated soils relies heavily on enzymatic activities as proxies for microbial function and soil health. This study evaluates the effectiveness of various organic and inorganic amendments—namely municipal waste, calcium oxide, Aspilia africana, and Eupatorium odorata—in enhancing enzymatic activities in used engine oil-contaminated soils. By applying mixed-effects models and enzyme kinetics analysis, we investigate the influence of treatments and substrate concentration on phosphatase, urease, dehydrogenase, and catalase activities. Our findings highlight municipal waste as the most effective treatment, consistently yielding the highest enzymatic velocities and catalytic efficiencies over 126 days. Mixed-effects models provided robust insight into fixed and random effects, capturing variability across time and treatments. This work demonstrates the potential of integrating statistical modeling with biochemical assessments to optimize bioremediation strategies.