Research Progress on Seed Appearance Recognition for Major Crops

The appearance characteristics of crop seeds can provide information about the quality, size, and variety of seeds. Through continuous research on seed appearance recognition technology, automated grading and screening of large-scale seed samples can be realized to ensure the purity and consistency of seeds and improve the quality and efficiency of crop production and breeding. Therefore, strict quality testing and identification of crop seeds are key factors in ensuring high yield, high quality, and crop safety. Currently, the main categories of appearance recognition technology include manual recognition, machine vision technology, and spectral imaging technology. Machine vision technology simulates the visual function of the human eye and combines image processing and analysis algorithms to achieve rapid and accurate identification of seed appearance characteristics. Spectral imaging technology, specifically near-infrared spectroscopy (NIR), analyzes the spectral information on the surface of seeds to reveal their internal chemical composition and structural characteristics, enabling non-destructive detection of seed varieties and quality. The application of machine vision recognition technology and spectral imaging technology provides a new solution for crop seed appearance recognition, improving the accuracy and efficiency of seed recognition and promoting the optimization of the agricultural production chain and the competitiveness of agricultural products in the market.