Optimization and application of bacterial consortia for enhanced bioremediation of dairy industry effluent using Box-Behnken design

This study optimized and evaluated a bacterial consortium for treating dairy industry effluent. Effluent samples collected from a dairy processing facility in Nigeria were analyzed for physicochemical parameters and heavy metal concentrations. Bacterial isolates were screened, identified and tested for compatibility before developing a consortium. Bioremediation conditions were optimized using experimental design, focusing on molasses concentration, temperature, pH and inoculum size. The optimal conditions for total organic carbon degradation were a molasses concentration of 0.60 mg/L, a temperature of 32°C, pH 7.7, and an inoculum size of 17 mL. Under these conditions, total organic carbon decreased from 520 mg/L to 43.6 mg/L, chemical oxygen demand reduced from 1,480 mg/L to 120 mg/L, and biochemical oxygen demand declined from 780 mg/L to 65 mg/L, demonstrating significant pollutant removal. Carbon dioxide evolution increased steadily, reflecting active microbial metabolism, while enzyme activities peaked around day 10, correlating with enhanced bacterial proliferation and subsequent nutrient depletion. The regression model exhibited a high predictive accuracy, with an R² value of 0.9997, confirming the reliability of the bioremediation process. These findings underscore the effectiveness of the optimized bacterial consortium in degrading organic pollutants in dairy effluent. The study highlights the potential application of microbial consortia in industrial wastewater treatment, providing a sustainable and efficient approach to reducing environmental pollution.

Authors

Publication Details

Journal
KIU journal of science engineering and technology
Published
2025-05-25
DOI
https://doi.org/10.59568/kjset-2025-4-1-26
Primary Topic
Microbial Community Ecology and Physiology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimization and application of bacterial consortia for enhanced bioremediation of dairy industry effluent using Box-Behnken design

Ajao A.T, A. John Presin Kumar, A B, Adegbola G.M. Eniola K.I.T
1 links
KIU journal of science engineering and technology
Microbial Community Ecology and Physiology
article

Optimization and application of bacterial consortia for enhanced bioremediation of dairy industry effluent using Box-Behnken design

Ajao A.T, A. John Presin Kumar, A B, Adegbola G.M. Eniola K.I.T
article en

Abstract

This study optimized and evaluated a bacterial consortium for treating dairy industry effluent. Effluent samples collected from a dairy processing facility in Nigeria were analyzed for physicochemical parameters and heavy metal concentrations. Bacterial isolates were screened, identified and tested for compatibility before developing a consortium. Bioremediation conditions were optimized using experimental design, focusing on molasses concentration, temperature, pH and inoculum size. The optimal conditions for total organic carbon degradation were a molasses concentration of 0.60 mg/L, a temperature of 32°C, pH 7.7, and an inoculum size of 17 mL. Under these conditions, total organic carbon decreased from 520 mg/L to 43.6 mg/L, chemical oxygen demand reduced from 1,480 mg/L to 120 mg/L, and biochemical oxygen demand declined from 780 mg/L to 65 mg/L, demonstrating significant pollutant removal. Carbon dioxide evolution increased steadily, reflecting active microbial metabolism, while enzyme activities peaked around day 10, correlating with enhanced bacterial proliferation and subsequent nutrient depletion. The regression model exhibited a high predictive accuracy, with an R² value of 0.9997, confirming the reliability of the bioremediation process. These findings underscore the effectiveness of the optimized bacterial consortium in degrading organic pollutants in dairy effluent. The study highlights the potential application of microbial consortia in industrial wastewater treatment, providing a sustainable and efficient approach to reducing environmental pollution.

KIU journal of science engineering and technologyVol. 4(1)
Openalex Percentile: Top 82%
Microbial Community Ecology and Physiology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.