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• W4386361167 abstract "Tea has an important socioeconomic status in China and other countries around the world. Relative chlorophyll content (Soil and plant analyzer development, SPAD) is one of the most commonly used indicators for measuring the growth status of tea plants. However, we believe further research is still needed on collectingspectral characteristics of tea tree SPAD based on multispectral UAV images and the data collected on tea tree sample plots. Therefore, two repeated field experiments were conducted in the tea garden of South China Agricultural University. The ground sample survey method was specifically adopted in the experiments using rectangular boxes to identify sample plots. During the mild pruning period of the tea tree canopy, multispectral UAV images were obtained and SPAD values of tea tree canopy leaves were synchronously measured. Then, an analysis was conducted on the correlation of spectral information and vegetation index obtained from the multispectral UAV images with SPAD, so that the spectral parameters with higher correlation were selected to construct the inversion model of the multivariate linear stepwise regression model (MLSR) for further accuracy evaluations. Research results show that: (1) Obtaining the average SPAD values of the plots by identifying plots with rectangular boxes can ensure the correspondence between the sample plots and the multispectral UAV images, which is a more suitable ground survey method for inverting vegetation canopy SPAD values using multispectral UAVs. (2) The MLSR model owns high accuracy and is more stable in prediction. The $R^{2}$, RMSE, and Re of its test sample set were 0.865, 3.5481, and 4.2481%, respectively. The spatial inversion distribution map of SPAD in the research area was obtained for the statistical analysis on the measured values and inversion values. The SPAD inversion values were between 50-88.3, accounting for 99.04%; the overall SPAD inversion values were consistent with the measured results. In this study, more accurate methods were used to obtain ground data. Combined with selected spectral parameters, they help construct a better tea tree SPAD inversion model, which can provide certain assistance for monitoring tea tree growth. Inversion model of multiple linear stepwise regression model was constructed during the mild pruning period of tea tree canopy, which is more in line with the dynamic growth law of tea tree and more realistically reflects the spatial distribution inversion of SPAD in the research area." @default.
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• W4386361167 date "2023-07-25" @default.
• W4386361167 modified "2023-09-27" @default.
• W4386361167 title "Estimation of Chlorophyll Content of Tea Tree Canopy using multispectral UAV images" @default.
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• W4386361167 doi "https://doi.org/10.1109/agro-geoinformatics59224.2023.10233406" @default.
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