In agriculture, seed and fruit quality checking is often done manually through visual inspection. This process is slow, inaccurate, and inconsistent, often leading to missed detection of internal damage or poor-quality seeds. As a result, farmers face post-harvest losses of 20–30% due to ineffective grading and quality assessment. The lack of affordable technology for small and medium-scale farmers worsens this issue, creating inefficiency in the supply chain.

Seed2Fruit addresses this by offering a portable, AI-driven system that uses computer vision and deep learning (CNN models) integrated with a Raspberry Pi camera to analyze seed and fruit quality in real time. It provides accurate, low-cost, and automated quality detection—reducing human error and dependency on lab-based testing. This innovation empowers farmers with data-driven decision-making tools, minimizing waste and increasing productivity.