Research Keyword: statistical optimization

Production, optimization and characterization of esterase isolated from a new endophytic Trichoderma afroharzianum strain AUMC 16,433 and its applications in dye decolorization

Scientists discovered a new type of fungus that produces an enzyme capable of breaking down synthetic dyes used in the textile industry. Using statistical optimization techniques, they enhanced the enzyme’s production and purified it to study its properties. The enzyme successfully removed various industrial dyes from solutions, with the highest effectiveness on malachite green dye. This discovery offers a promising natural solution to reduce environmental pollution caused by textile dye wastewater.

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Nano-bioremediation of metal-polluted industrial wastewater using myco-synthesized iron oxide nanoparticles derived from Aspergillus niger AUMC 16028

Scientists have developed a green method to clean polluted industrial water using specially grown fungal nanoparticles. These tiny iron particles, made from Aspergillus niger fungus, can effectively remove dangerous heavy metals like copper, zinc, and iron from contaminated water. This eco-friendly approach is cheaper and safer than traditional chemical methods, offering a promising solution for protecting our water resources.

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