There are many types of date fruit, each with similar physical properties and slight differ- ences in color,shape and fleshiness among other characteristics.It can be challenging and time consuming for an individual to distinguish between the different types of dates due to the myriad of attributes to consider.The objective of this study was to employ the Deep Learning technology the You Only Look Once (YOLO) algorithm, for image detection,classification and provision of nutritional information about date fruits.Subsequently,the YOLO object detection model was trained using the YOLOv5,YOLOv7 and YOLOv8 algorithms on Google Colaboratory’s cloud service,utilizing the Kaggle dataset, which comprises 1735 images of 9 different types of date fruit. An accuracy analysis of these three algorithms was conducted based on Recall,Precision and F1-score metrics the results were subsequently compared.The experimental results demon- strate that YOLOv8 achieves IoU between [0-1],an mAP@0.5 and mAP@[0.5:0.95] of 0.99%,a Recall of 0.997% and a Precision of 0.991%.