Banana bunch image and video dataset for variety classification and grading

Abstract

Banana, a major commercial fruit crop, holds high nutritional value and widespread consumption [[4], [8],10]. The global banana market valued at USD 140.83 billion in 2024 is projected to reach USD 147.74 billion by 2030. Accurate variety identification and quality grading are crucial for marketing, pricing, and operational efficiency in food processing industries [9]. As wholesalers and food processing industries process bananas in bunches (not individual fruit levels) , our bunch-level dataset offers a more accurate assessment by capturing bunch-level characteristics, which are vital for grading. Existing datasets, such as [1,6], focus on individual bananas or have limited bunch-level data, highlighting the lack of large-scale bunch datasets. This dataset fills the gap by providing bunch-level images and videos of three widely consumed banana varieties-Elakki-bale, Pachbale, and Rasbale, from Mysuru, South Karnataka, India, serving as a valuable resource for food processing industries. Our dataset supports training machine learning models for bunch-level variety classification and grading of bananas and serves as a resource for research and education.