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Remote Sensing Inversion of Nitrogen Nutrition Status of Apple Tree Leaves during Stopping Period of Spring Shoots
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作者 Tianlin Liu Xicun Zhu +4 位作者 Xueyuan Bai Yufeng Peng Zhongyu Tian Meixuan Li Yuanmao Jiang 《遥感科学(中英文版)》 2020年第1期1-8,共8页
The nutrient inversion model of apple leaves was established by spectral analysis technology to provide technical support for the fine management of apple trees.In Shuangquan Town,Changqing District,Jinan City,Shandon... The nutrient inversion model of apple leaves was established by spectral analysis technology to provide technical support for the fine management of apple trees.In Shuangquan Town,Changqing District,Jinan City,Shandong Province,the Fuji apple trees with stopping period of spring shoots were taken as research objects.The spectral reflectance and nitrogen content of apple leaves were measured by ASD Field Spec 4 portable ground object spectrometer.Analyzed the correlation between leaf nitrogen content and spectral reflectance.The sensitive wavelengths with high correlation coefficient were select by fractional differential algorithm,and the optimal vegetation index was constructed and screened out.Partial Least Square Regression(PLSR),Support Vector Machine(SVM)and Random Forests(RF)method were used to construct an inversion model of leaf nitrogen content.The results show that the RF model based on fractional differential second-order treatment is the best inversion model for the nitrogen content of leaves during stopping period of spring shoots.The modeling accuracy determination coefficient R2 reached 0.891,RMSE was 0.0841,and RPD was 2.1396.The determination coefficient R2 of the fitting results of the verification set was 0.617,RMSE was 0.1251,and RPD was 1.7105.The inversion model established by RF method is effective in monitoring the nitrogen content in apple leaves,which provides a theoretical basis for monitoring the growth of apple by hyperspectral technology. 展开更多
关键词 Apple Tree Stopping period of Spring Shoots Nitrogen Nutrition Remote Sensing Inversion
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