Abstract: As an emerging technical means, high-throughput phenotyping (HTP) of crops aims to quickly and accurately reveal the relationship between crop traits and genes as well as environment by analyzing a large amount of phenotypic data, thereby optimizing breeding efficiency and accuracy, and improving crop yield and quality, solving the problem of increased demand for food in the context of increasing global population and environmental deterioration. After analyzing the key technical architecture of HTP of crops, the methods and shortcomings of collecting, sorting and analyzing crop phenotypic information are explained from the aspects of sensors, multi-scale observation and big data mining. On this basis, the main application areas of crop phenotyping analysis in recent years were reviewed. The study confirmed that crop HTP analysis is an effective tool for quantifying crop traits, monitoring crop growth, optimizing field management, and improving breeding efficiency. However, there is potential for the improvement of its application performance. Finally, the challenges, optimization solutions, broad prospects and future development trends of HTP phenotyping of crops were discussed. It shows that there are still challenges in data processing and analysis, cross-species, cross-organization, and cross-environment applications. However, with the increasing development of cutting-edge technologies such as cloud big data processing platforms and artificial intelligence, which have great advantages in processing large-volume and high-complexity data, combined with biotechnology and genomics research methods, HTP of crops will play a pivotal role in combating food shortages caused by global environmental changes and population increase.