This dataset supports the research project titled: "Development of cost-effective process for phyco-remediation of dairy wastewater and valorization of algal biomass for production of biofuel and biochemical: A sustainable approach towards bio-refinery."

Purpose: The dataset was generated to explore sustainable strategies for wastewater treatment and biomass valorization using microalgae-based systems. It aims to enable resource recovery from dairy wastewater through integrated remediation and bio-conversion processes.

Nature: The dataset is organized into three sections, each corresponding to a key objective of the project:

Objective 1 – Phyco-remediation of dairy wastewater (DW): Includes experimental data on the design and performance of microalgae consortia for DW treatment. This section supports the published article: Co-Cultivation of High-Value Microalgae Species with Filamentous Microalgae for Dairy Wastewater Treatment.

Objective 2 – Valorization via hydrolysis: Contains data on the synthesis and characterization of a multienzyme magnetic nanocatalyst (ME-MNC) for the hydrolysis of microalgal biomass. Data include enzyme immobilization optimization, material characterization (XRD, FTIR, FESEM, TGA), and recovery of sugars and proteins.

Objective 3 – Biochemical and biofuel production: Presents data from fermentation experiments using hydrolyzed biomass as feedstock. It compares the performance of free and immobilized Actinobacillus succinogenes cells in producing organic acids, including yield and reusability.

Scope: The dataset covers raw measurements, processed data, and supporting documentation for all three project objectives. It includes metadata, analysis outputs, and experimental protocols. Refer to the folder structure for details on specific contents and conditions.