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Ujjain SVVU Science Bazaar Showcases 16 Student Projects, Millet-Based Foods And Algae Biofuel Innovation

Ujjain (Madhya Pradesh): Samrat Vikramaditya Vishwavidyalaya, Ujjain (SVVU), organised 'Colors of Science 3.0 - Vigyan Bazaar' on Friday at its School of Studies in Zoology and Biotechnology. The event, themed 'Science for Farmer Welfare', was organised under the Madhya Pradesh government's 'Kisan Kalyan Year 2026' initiative to connect science with society, agriculture and daily life while…

Ujjain SVVU Science Bazaar Showcases 16 Student Projects, Millet-Based Foods And Algae Biofuel Innovation

Samrat Vikramaditya Vishwavidyalaya (SVVU) in Ujjain, Madhya Pradesh, hosted the Colors of Science 3.0 - Vigyan Bazaar on Friday, showcasing 16 student science projects at its School of Studies in Zoology and Biotechnology. The event, themed "Science for Farmer Welfare," aimed to connect science with society, agriculture, and daily life, aligning with Madhya Pradesh's Kisan Kalyan Year 2026 initiative.

Vice-chancellor Dr Arpan Bhardwaj inaugurated the fair, which attracted over 12 university departments, students, and faculty from Navodaya Vidyalaya Ghattiya, Virgin Mary School, and Gyan Sagar Academy.

The bazaar featured 25 food stalls, 15 Bio-informatics and Chemistry (BIC) stalls, and 16 student science projects. Visitors appreciated the participants' efforts, particularly the millet-based nutritious dishes and food innovation displayed by the students. In the food competition, Sampurna won first place, Narish & Flourish secured second, and Biotech Trades took third.

The agriculture category's standout project was the Algae Biofuel Model by Ankit, Pushpa, Ekta, Divya, and Jadav, who won first position. Ananya Rathore secured second place in forensic science for her experiment on forensic psychology and memory. Students from various schools and institutions participated, highlighting the practical learning and entrepreneurial opportunities generated by the event.

Written by urgent.news from Free Press Journal's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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