Review of the application of in-situ sensing techniques to address the tea growth characteristics from leaf to field

Qiong Cao, Chunjiang Zhao, Ze Xu, Ping Jiang, Haibin Yang, Xiangyu Meng, Guijun Yang

Abstract


The tea plant is a valuable and evergreen crop that is extensively cultivated in China and many other countries. Currently, there is growing research interest in this plant. For the tea industry, it is crucial to develop rapid and non-invasive methods to evaluate tea plants in their natural environment. This article provides a comprehensive overview of non-invasive sensing techniques used for in-situ detection of tea plants. The topics covered include leaf, canopy, and field-level assessments, as well as statistical analysis techniques and characteristics specific to the research. Non-invasive testing technology is primarily used for monitoring and predicting tea pests and diseases, monitoring quality, and nutrients, determining tenderness and grade, identifying tea plant varieties, automatically detecting, and identifying tea buds, monitoring tea plant growth, and extracting tea garden areas through remote sensing. It also helps to evaluate planting suitability, assess disasters, and estimate yields. Additionally, the article examines the challenges and prospects of emerging techniques aimed at resolving the in-situ detection problem for tea plants. It can assist researchers and producers in comprehensively understanding the tea environment, quality characteristics, and growth process, thereby enhancing tea production quality, and fostering tea industry development.
Keywords: non-destructive, in-situ detection, tea plants, growth characteristics, sensors
DOI: 10.25165/j.ijabe.20241701.8395

Citation: Cao Q, Zhao C J, Xu Z, Jiang P, Yang H B, Meng X Y, et al. Review of the application of in-situ sensing techniques to address the tea growth characteristics from leaf to field. Int J Agric & Biol Eng, 2024; 17(1): 1-11.

Keywords


non-destructive, in-situ detection, tea plants, growth characteristics, sensors

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References


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