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  • Open Access

    ARTICLE

    Monitoring Thosea sinensis Walker in Tea Plantations Based on UAV Multi-Spectral Image

    Lin Yuan1, Qimeng Yu1, Yao Zhang2,*, Xiaochang Wang3, Ouguan Xu1, Wenjing Li1

    Phyton-International Journal of Experimental Botany, Vol.92, No.3, pp. 747-761, 2023, DOI:10.32604/phyton.2023.025502 - 29 November 2022

    Abstract Thosea sinensis Walker (TSW) rapidly spreads and severely damages the tea plants. Therefore, finding a reliable operational method for identifying the TSW-damaged areas via remote sensing has been a focus of a research community. Such methods also enable us to calculate the precise application of pesticides and prevent the subsequent spread of the pests. In this work, based on the unmanned aerial vehicle (UAV) platform, five band images of multispectral red-edge camera were obtained and used for monitoring the TSW in tea plantations. By combining the minimum redundancy maximum relevance (mRMR) with the selected spectral features,… More >

  • Open Access

    ARTICLE

    Tea Plantation Frost Damage Early Warning Using a Two-Fold Method for Temperature Prediction

    Zhengyu Wu1, Kaiqiang Li1, Lin Yuan2, Jingcheng Zhang1, Xianfeng Zhou1,*, Dongmei Chen1,*, Kaihua Wei1

    Phyton-International Journal of Experimental Botany, Vol.91, No.10, pp. 2269-2282, 2022, DOI:10.32604/phyton.2022.022607 - 30 May 2022

    Abstract As the source and main producing area of tea in the world, China has formed unique tea culture, and achieved remarkable economic benefits. However, frequent meteorological disasters, particularly low temperature frost damage in late spring has seriously threatened the growth status of tea trees and caused quality and yield reduction of tea industry. Thus, timely and accurate early warning of frost damage occurrence in specific tea garden is very important for tea plantation management and economic values. Aiming at the problems existing in current meteorological disaster forecasting methods, such as difficulty in obtaining massive meteorological… More >

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