The agricultural industry has witnessed transformative advances with the integration of digital technologies into quality assessment and processing. Online perception technology, which encompasses an array of sensor modalities, imaging techniques, and intelligent data processing algorithms, has emerged as a pivotal tool in ensuring the quality, safety, and marketability of agricultural products. A comprehensive survey of recent research progress in the field was provided, focusing on the application of online perception systems for agricultural product quality assessment. The technological components underpinning these systems were critically analyzed, including machine vision, hyperspectral imaging, near-infrared spectroscopy, and advanced data analytics. The discussion covered the evolution of sensor hardware, algorithmic developments in machine learning and deep learning, and the integration of multi-modal data for real-time quality control. Specific application examples were presented across different categories, such as fruit and vegetable sorting, grain quality monitoring, and the evaluation of meat and dairy products. The future trends and the potential of emerging technologies were also outlined to further revolutionize the perception of agricultural quality perception technologies. In summary, it highlighted how online perception technologies not only enhanced the precision and efficiency of quality assessment but also contributed to sustainable practices by reducing wastage and ensuring compliance with safety standards.