Betel Leaf Dataset: A Primary Dataset From Field And Controlled Environment

Betel leaves hold high value due to its culinary, medical, and religious values. Future potential for better quality control, yield, and sustainable cultivation may derive from understanding the growth habits of the plant, its disease-resisting capabilities, and farming conditions. The dataset comprises betel leaf images. After reviewing the existing databases in the literature, it has been observed that very few researchers have explored the betel leaf. The available datasets are not up to the mark as they consist of images in the field. Also, along with it, the dried leaves class was not considered. The authors addressed these gaps in this dataset by acquiring betel leaf images from both on-field and controlled environments. Also, dried images of betel leaves were acquired. It has three classes, namely healthy, diseased, and dried. The dataset acquired was from the betel leaf cultivation farms in Maharashtra with the help of agronomists. The images are acquired from the field and in a controlled environment. A total of 1800 images were captured with a high-resolution camera in jpeg format. Out of 1800, healthy leaves samples are 669, dried leaves are 622, and diseased 509. The dataset can also be used by researchers to discover betel leaf ailments and estimate the severity of such diseases using artificial intelligence techniques.