Extraction strategies integrated with digitalization processes for the characterization of proteins from broad bean and red beetroot waste leaves

A real-time monitored Internet of Things (IoT)-integrated ultrasound-assisted extraction laboratory-scale prototype was developed and evaluated as a green and scalable processing platform for the recovery of high-value compounds from food-grade plant by-products. The key novelty of this study lies in the integration of IoT-based process monitoring and control with ultrasound-assisted extraction, enabling reproducible and energy-efficient recovery of proteins and bioactive compounds from plant matrices. Leaves of Vicia faba L. (broad bean) and Beta vulgaris L. (red beetroot), characterized by a protein content exceeding 30% of dry matter, were selected as representative raw materials. Ultrasound-assisted aqueous extraction yielded protein-rich extracts with mildly acidic pH values (5.94-6.81) and low electrical conductivity (0.043-4.355 mS/cm), indicating minimal matrix degradation and favourable processing conditions. The extracts contained water-soluble flavonoids, free amino acids, and proteins at concentrations suitable for further food and bioproduct applications. Proteomic profiling by nanoLC-MS/MS revealed the presence of ribulose-1,5-bisphosphate carboxylase/oxygenase as the dominant chloroplast protein, alongside hundreds of additional water-soluble proteins originating from multiple plant cell compartments, confirming the broad extraction capability of the ultrasound-assisted system. Continuous IoT-based monitoring ensured stable operating conditions and process reproducibility throughout extraction. The results demonstrate that the proposed IoTenabled ultrasound-assisted extraction prototype represents an effective green technology for the valorisation of plant-based by-products and shows strong potential for process optimization and scale-up toward industrial applications.