Furthermore, this dataset can be instrumental in other areas such as quality control, supply chain management, and precision farming. For instance, researchers and developers can use this dataset to enhance the efficiency and accuracy of automated harvesting systems, which reduces labor costs and increases productivity. Additionally, the diverse range of images, covering different stages of tomato ripeness, ensures comprehensive model training and evaluation. Consequently, this contributes to the advancement of smart farming solutions.