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Estimation of the leaf chlorophyll content using multiangular spectral reflectance factor
Author(s) -
Li Wange,
Sun Zhongqiu,
Lu Shan,
Omasa Kenji
Publication year - 2019
Publication title -
plant, cell and environment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.646
H-Index - 200
eISSN - 1365-3040
pISSN - 0140-7791
DOI - 10.1111/pce.13605
Subject(s) - reflectivity , chlorophyll , reflection (computer programming) , remote sensing , photochemical reflectance index , plant species , content (measure theory) , spectral properties , spectral index , mathematics , biological system , botany , environmental science , optics , chemistry , spectral line , computer science , biology , physics , geology , chlorophyll fluorescence , mathematical analysis , computational chemistry , astronomy , programming language
Chlorophyll is one of the primary pigments of plant leaves, and changes in its content can be used to characterize the physiological status of plants. Spectral indices have been devised and validated for estimating leaf chlorophyll content (LCC). However, most of the existing spectral indices do not consider the influence of angular reflection on the accuracy of the LCC estimation. In this study, the spectral reflectance factors of leaves from three plant species were measured from several observations in the principal plane. The relationship between the existing spectral indices and the LCC from different directions suggests that the directional reflection of a leaf surface impacts the accuracy of its LCC estimation. Subsequently, the ratio of reflectance differences, that is, the modified Datt index, was tested to reduce the directional reflection effect when predicting LCC. Our results indicated that the modified Datt index not only estimated LCC with high accuracy for all observation directions and plant species but also consistently predicted the LCC of each species in individual observation directions. Our method opens the possibility for optical detection of LCC using multiangular spectral reflection, which is convenient for plant science studies focused on the variation in LCC.