Rapid detection of chlorophyll content and distribution in citrus orchards based on low-altitude remote sensing and bio-sensors

作     者：Kejian Wang Wentao Li Lie Deng Qiang Lyu Yongqiang Zheng Shilai Yi Rangjin Xie Yanyan Ma Shaolan He 

作者机构：Citrus Research Institute of Chinese Academy of Agricultural SciencesSouthwest UniversityBeibeiChongqing 400712China 

出 版 物：《International Journal of Agricultural and Biological Engineering》 (国际农业与生物工程学报（英文）)

年 卷 期：2018年第11卷第2期

页      面：164-169页

核心收录：

学科分类：0710[理学-生物学] 071001[理学-植物学] 07[理学] 

基　　金：supported by the China National Key Research and Development Project(2016YFD0200703) the China National Science&Technology Support Program(2014BAD16B0103) the China Chongqing Science&Technology Support&Demonstration Project(CSTC2014fazktpt80015) the Jiangxi Province 2011 Collaborative Innovation Special Funds“Co-Innovation Center of the South China Mountain Orchard Intelligent Management Technology and Equipment”(Jiangxi Finance Refers toNo.156) 

主　　题：citrus remote sensing bio-sensor chlorophyll detection spectrum ratio vegetation index(RVI) normalized differential vegetation index(NDVI) spatial distribution map 

摘      要：The accuracy of detecting the chlorophyll content in the canopy and leaves of citrus plants based on sensors with different scales and prediction models was investigated for the establishment of an easy and highly-efficient real-time nutrition diagnosis technology in citrus *** fluorescent values of leaves and canopy based on the Multiplex 3.6 sensor,canopy hyperspectral reflectance data based on the FieldSpec4 radiometer and spectral reflectance based on low-altitude multispectral remote sensing were collected from leaves of Shatang mandarin and then ***,the associations of the leaf SPAD(soil and plant analyzer development)value with the ratio vegetation index(RVI)and normalized differential vegetation index(NDVI)were *** leaf SPAD value predictive model was established by means of univariate and multiple linear regressions and the partial least squares *** distribution maps of the relative canopy chlorophyll content based on spectral reflectance in the orchard were automatically *** results showed that the correlations of the SPAD values obtained from the Multiplex 3.6 sensor,FieldSpec4 radiometer and low-altitude multispectral remote sensing were highly *** measures of goodness of fit of the predictive models were R^(2)=0.7063,RMSECV=3.7892,RE=5.96%,and RMSEP=3.7760 based on RVI_((570/800)) and R^(2)=0.7343,RMSECV=3.6535,RE=5.49%,and RMSEP=3.3578 based on NDVI[(570,800)(570,950)(700,840)].The technique to create spatial distribution maps of the relative canopy chlorophyll content in the orchard was established based on sensor information that directly reflected the chlorophyll content of the plants in different parts of the orchard,which in turn provides evidence for implementation of orchard productivity evaluation and precision in fertilization management.