Dataset for digital of good and bad classes of kheerShapathi Mango(Mangifera indica) slices.
Description
This dataset contains digital images of fresh-cut kheerShapathi mango (Mangifera indica L.) slices collected under room temperature conditions for shelf-life analysis. The objective of this dataset is to observe the visual changes occurring in fresh-cut mango slices during storage and to classify the images into Good and Bad quality categories. One ripe kheerShapathi mango was selected and peeled manually using a stainless steel knife. The mango pulp was cut into five pieces and each piece was placed separately on a white plastic plate. Images of both the front and back sides of each mango piece were captured using a Redmi 9 smartphone camera (13MP+2MP rear primary camera). The photographs were taken on a white background under indoor room conditions with artificial lighting. The samples were kept at approximately 30°C room temperature. The mango pieces were placed on a table and remained exposed to ambient conditions during the experiment. Image acquisition started at 10:00 AM on the first day and continued until 1:00 AM. On the second day, image collection resumed from 9:00 AM to 11:00 AM. During the first day, images were captured at 10-minute intervals, while on the second day images were captured at 15-minute intervals. A total of 1100 images were collected: 550 Good images 550 Bad images Visual deterioration of mango slices, including browning, color change, and surface quality degradation, started approximately at 6:00 PM on the first day. Images showing fresh appearance were categorized as Good, while images showing visible deterioration were categorized as Bad. Materials Used: kheerShapathi mango Stainless steel knife White plastic plates White background sheet Table surface Redmi 9 smartphone camera This dataset can be used for image processing, machine learning, computer vision, and shelf-life prediction studies of fresh-cut mango slices.