Mobile app for detecting of potential bud fruitfulness: A tool for predicting

Abstract: The budding process in grape cultivation is a crucial stage that significantly influences the quality and yield of grape harvests. This abstract introduces an innovative approach that combines the power of the YOLOv8 algorithm with a mobile application to enhance the detection and monitoring of grape buds during the budding process.

High-resolution images of grapevines in various budding stages are captured using imaging tools and these images are processed through the YOLOv8 algorithm. This state-of-the-art object detection system excels at accurately identifying grape buds and categorizing them based on their developmental stages, including dormant, swelling, green tip, and advanced growth phases.

Here we are doing the integration of a user-friendly mobile app. The application provides Grape growers and vineyard managers with real-time access to the YOLOv8-based detection system. This empowers users to view, analyze, and track grape bud development directly from their mobile devices. It also allows for immediate decision-making, as users can time vital tasks such as pruning, irrigation, and disease management with precision.

In conclusion, the fusion of the YOLOv8 algorithm with a user-friendly mobile application for grape bud detection in the budding process is a groundbreaking advancement in precision viticulture. This innovative solution not only improves the accuracy of bud detection but also offers accessible and data-driven vineyard management. The research presented here opens new horizons for grape cultivation, benefiting both the viticulture industry and the broader agricultural community.

Keywords: Segmentation, Bud’s Detection, Final work on App, YOLOv8 algorithm.