The Dawn of Intelligent Technologies in Tea Industry

Background: Tea is a globally significant agricultural product, renowned for its economic and cultural value. The process of tea cultivation and production involves tea plantation management, disease control, harvesting, processing, sorting and safety and quality assessment. The quality of tea can be affected by many factors, involving variety, environment, picking and processing. Nevertheless, quality assessment of tea often relies on manual experience and specialized knowledge, which is accompanied by subjectivity and inconsistency. Furthermore, the tea production process also faces several challenges, such as pest and disease prediction and detection, supply chain monitoring and traceability. Scope and approach: This review introduces intelligent technologies applied in tea industry, including computer vision, machine learning, spectroscopic techniques, artificial sensors, big data, internet of things, and blockchain. We summarize the progress of the application of intelligent technologies in tea industry, analyze the existing challenges and gaps, and suggest future research trends. The review is expected to provide novel insights into the application of intelligent technologies in tea industry to build a transparent, traceable, and sustainable tea industry chain. Key findings and conclusions: Intelligent technologies have a broad application prospect in tea industry to improve product quality, efficiency, transparency, and traceability. Particularly, combination of intelligent technologies may result in better performance. Open datasets are necessary for storage of huge amount of information. Standardization of intelligent technologies establishes a solid foundation for development of sustainable tea industry. Furthermore, transition to portable devices is the most responsive direction to tea market demands.