文献类型： 外文期刊
作者： Li, Dan 1 ; Wang, Chongyang 1 ; Jiang, Hao 1 ; Peng, Zhiping 2 ; Yang, Ji 1 ; Su, Yongxian 1 ; Song, Jia 3 ; Chen, Shuise 1 ;
作者机构： 1.Guangzhou Inst Geog, Guangdong Key Lab Remote Sensing & GIS Applicat, Guangdong Open Lab Geospatial Informat Technol &, Guangzhou 510070, Guangdong, Peoples R China
2.Guangdong Acad Agr Sci, Inst Agr Resources & Environm, Guangzhou 510640, Guangdong, Peoples R China
3.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China
关键词： Canopy; Growth stage; Litchi; Phosphorus; Spectral index
期刊名称：COMPUTERS AND ELECTRONICS IN AGRICULTURE （ 影响因子：5.565； 五年影响因子：5.494 ）
ISSN： 0168-1699
年卷期： 2018 年 154 卷
页码：
收录情况： SCI
摘要： Phosphorus (P) is an important element to litchi yield and fruit quality in addition to nitrogen (N) and potassium (K). This study was undertaken to explore the ability to predict P content using canopy reflectance. Some published indices and two ratio spectral indices (Ratio of reflectance index, RRI; Ratio of reflectance difference index, RRDI) developed by band interactive-optimization algorithms were investigated to determine their performance in predicting litchi canopy foliar P content. The results showed that optimal spectral indices selected by correlation analyses reached the highest level of accuracy in the retrieval of P content at each growth stage (R(2)cv = 0.54-0.98, RMSEcv = 0.02-0.03). The particular wavelengths of importance in the significant RRIs and RRDIs changed with the growing stages, cultivars and planting conditions. The sensitive wavebands ranged from the visible to the short-wave infrared (SWIR) regions, which are related to the absorption features of pigments (e.g., anthocyanin, chlorophyll), proteins, nitrogen, starch, sugar, oil, cellulose, and lignin. And the wavebands in SWIR region were used in the optimal RRIs and RRDIs for growth stages. This study demonstrates that the optimal RRDI is useful in predicting litchi foliar P content. The successes of use of SWIR in foliar nutrient monitoring is important for precision agriculture.
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