FRUIT Produce SMOOTHIE

Research on fruit processing and analysis is rapidly advancing, driven by the need for increased agricultural efficiency and improved food quality control. Current efforts focus on developing automated systems for tasks such as fruit harvesting, classification, and ripeness assessment, employing computer vision techniques, deep learning models (including neural architecture search), and sensor fusion (e.g., LiDAR and RGB cameras). These advancements aim to improve crop yield prediction, optimize harvesting processes, and enhance the overall efficiency and precision of fruit production and processing, ultimately impacting food security and reducing labor costs.