Berhampur: Two scholars in Berhampur University (BU) were awarded in the State-Level Innovation and Startup Competition-2025 for their innovations at a function held at Bhubaneswar on Saturday. The govt gave Rs 5 lakh cash reward to each of the 10 selected startups from different universities in the competition. Of those, two were bagged by the scholars of Berhampur University. “We are proud of our students’ success,” Berhampur University vice-chancellor Geetanjali Dash said on Sunday. The award money will help to improve their projects, she said.A total of 70 startup projects from 14 universities took part in the two-day state-level competition, concluded on Saturday and 10 of them were awarded. Higher education minister Suryabansi Suraj and former VC, GM University, Sambalpur A K Pati handed over the cash to the awarded scholars. Sandeep Kumar Dash, assistant professor, zoology-cum-coordinator of the programme in Berhampur University, said Archita Lenka, a research scholar in zoology and Ganeswar Khadenga, a student of physics in the university, received awards for their innovations. Lenka is working on sustainable bioactive ingredients and has drawn attention for its project to synthesise ellagic acid from casuarictin, tannin extracted from naturally fallen casuarinas litter, which is found along sea beaches. “The technology converts beach litter biomass into a high-value compound known for its antioxidant, anti-inflammatory, anti-cancer and cardio protective properties,” he said. “With the global ellagic acid market projected to reach US$110 million by 2032 due to demand from the cosmetic and pharmaceutical sectors, Lenka’s startup is positioning as an ingredient supplier with cost advantaged natural ellagic acid to global formulators,” said Dash.Khadenga has developed a portable, non-invasive system for diabetes and cardiac health monitoring to enable frequent and long-term health tracking under the guidance of Sukant Tripathy, a physics professor. The device uses fingertip photoplethysmography (PPG) with multi-wavelength light to capture blood-flow signals, while on-device machine-learning–based anomaly detection helps reduce errors caused by motion or improper finger placement. From optical data, the system estimates HbA1c, traditionally measured through laboratory blood tests.A connected progressive web application visualises data, tracks health trends, analyses heart rhythm patterns and supports both personal and clinical use, enabling early detection without invasive blood sampling, he said. The jury members in the competition have appreciated both the projects, said Dash.
