Dataset for digital images of Good and bad classes of Lakshmanbhog Mango (Mangifera indica) slice
Description
This dataset contains digital images of fresh-cut Lakshmanbhog 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 Lakshmanbhog 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 Realme C25Y smartphone camera (50 MP 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 2:00 PM. During the first day, images were captured at 10-minute intervals, while on the second day images were captured at 30-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: Lakshmanbhog mango Stainless steel knife White plastic plates White background sheet Table surface Realme C25Y smartphone camera This dataset can be used for image processing, machine learning, computer vision, and shelf-life prediction studies of fresh-cut mango slices.