Core Insights - The research team at the Chinese Academy of Agricultural Sciences has developed a high-quality image database and model library for rapeseed, enabling real-time online measurement of rapeseed quality using computer vision and artificial intelligence [1] Group 1: Research and Development - Traditional methods for rapeseed quality detection rely on precision instruments and laboratory analysis, which are time-consuming and not suitable for large-scale, real-time testing [1] - The innovative "photo measurement" solution allows users to take a picture and upload it, with results available in 10 seconds, achieving an accuracy rate exceeding 88% and an average error within 5% [1] - The SeedVision software developed is compatible with both computer and mobile platforms, providing technical support for real-time online quality detection of rapeseed and other oilseed crops [1] Group 2: Funding and Intellectual Property - The research has received funding from several projects, including the "14th Five-Year" National Key Research and Development Program, the National Natural Science Foundation, and the Agricultural Science and Technology Innovation Project of the Chinese Academy of Agricultural Sciences [1] - The team has applied for three invention patents and one software copyright related to their findings [1]