SBIR Phase I: Apple Yield Mapping using Computer Vision

The broader impact/commercial potential of this project is the practical deployment of a computer-vision based yield estimation system in fruit orchards. This will provide fruit farmers with a useful tool in planning their harvest and sales, as well as in managing the long-term health of their plants. This will potentially reduce the inherent risk in fruit growing, thereby improving the affordability and availability of fresh fruit in the US. Better certainty may particularly help small growers, because they have less existing capability to manage risk. Furthermore, by allowing adoption of precision agriculture techniques techniques to high value crops, this project may help save water and contribute to reduction of runoff pollution from fertilizer and chemicals. This Small Business Innovation Research (SBIR) Phase I project addresses the problem of vision-based fruit detection and mapping of fruit, for purposes of yield mapping. The research objectives are to improve the commercial usability and robustness of existing yield-mapping approaches, so that they can be applied in production fruit orchards. The anticipated technical results of this project include demonstration of useful yield mapping of apples, in a variety of real world production orchard environments, in a variety of weather and lighting conditions.